| Recommendation |
ID |
Data Information |
Model Information |
Application Information |
Reference |
| Rank |
Total_Score |
Model_ID |
Dataset_Name |
Element_type |
Data_features |
Model_name |
Algorithm_name |
Prediction_type |
Code_source |
Study_types |
Disease_name |
Target_name |
Drug_name |
Interaction_type |
Recommended_Number |
PMID |
Journal |
Publication_Year |
| 1 |
90.6 |
1539 |
LRSSL |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 1 |
90.6 |
1539 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 1 |
90.6 |
1539 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Alzheimer's disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 1 |
90.6 |
1539 |
Ldataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Alzheimer's disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 1 |
90.6 |
1539 |
Ldataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 1 |
90.6 |
1539 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 1 |
90.6 |
1539 |
LRSSL |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Alzheimer's disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 1 |
90.6 |
1539 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/TheWall9/DRHGCN |
Case studies |
Alzheimer's disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
34378011 |
Brief Bioinform |
2021 |
| 2 |
87.8 |
2207 |
Dataset 3 |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
DRDSA (Drug Repositioning Deep Sparse Autoencoder) |
Deep sparse autoencoder,Deep feedforward neural network |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/HDVD |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 10 drugs |
38103130 |
Interdiscip Sci |
2024 |
| 2 |
87.8 |
2207 |
Dataset 4 |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
DRDSA (Drug Repositioning Deep Sparse Autoencoder) |
Deep sparse autoencoder,Deep feedforward neural network |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/HDVD |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 10 drugs |
38103130 |
Interdiscip Sci |
2024 |
| 2 |
87.8 |
2207 |
Dataset 1 |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
DRDSA (Drug Repositioning Deep Sparse Autoencoder) |
Deep sparse autoencoder,Deep feedforward neural network |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/HDVD |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 10 drugs |
38103130 |
Interdiscip Sci |
2024 |
| 2 |
87.8 |
2207 |
Dataset 2 |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
DRDSA (Drug Repositioning Deep Sparse Autoencoder) |
Deep sparse autoencoder,Deep feedforward neural network |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/HDVD |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 10 drugs |
38103130 |
Interdiscip Sci |
2024 |
| 3 |
86.5 |
1868 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
GLGMPNN |
Message Passing Neural Network (MPNN), Gated Fusion Mechanism |
Drug Disease Association (DDA) |
https://github.com/bdtree/GLGMPNN |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
36305457 |
Brief Bioinform |
2022 |
| 3 |
86.5 |
1868 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
GLGMPNN |
Message Passing Neural Network (MPNN), Gated Fusion Mechanism |
Drug Disease Association (DDA) |
https://github.com/bdtree/GLGMPNN |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
36305457 |
Brief Bioinform |
2022 |
| 4 |
85.4 |
815 |
Cdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
PREDICT (Fdataset) |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
NA |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
PREDICT (Fdataset) |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
NA |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
Cdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
PREDICT (Fdataset) |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
NA |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 4 |
85.4 |
815 |
Cdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
OMC |
Overlap Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/OMC |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
31869322 |
PLoS Comput Biol |
2019 |
| 5 |
85 |
1566 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Gabapentin |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Frovatriptan |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Gabapentin |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 5 |
85 |
1566 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
BGMSDDA |
K nearest known neighbors (WKNKN) |
Drug Disease Association (DDA) |
https://github.com/kk-2010000/BGMSDDA |
Case studies |
NA |
NA |
Frovatriptan |
NA |
Top 20 diseases |
34610633 |
Mol Omics |
2021 |
| 6 |
84.3 |
1807 |
NA |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
GCMM (Graph convolution network based on a multimodal attention mechanism) |
Convolutional Neural Network (CNN) |
Drug Disease Association (DDA) |
https://github.com/FanZhang0820/GCMM |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 5 drugs |
36100897 |
BMC Bioinformatics |
2022 |
| 7 |
84.04 |
289 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Cabergoline |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Cabergoline |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Cabergoline |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 7 |
84.04 |
289 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
MBiRW |
Random Walk |
Drug Disease Association (DDA) |
http://github.com//bioinfomaticsCSU/MBiRW |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
27153662 |
Bioinformatics |
2016 |
| 8 |
83.8 |
893 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
HNet-DNN |
Deep Neural Network (DNN) |
Drug Disease Association (DDA) |
https://github.com/hliu2016/HNet-DNN |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 15 drugs |
32118415 |
J Chem Inf Model |
2020 |
| 8 |
83.8 |
893 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
HNet-DNN |
Deep Neural Network (DNN) |
Drug Disease Association (DDA) |
https://github.com/hliu2016/HNet-DNN |
Case studies |
NA |
NA |
Enalapril |
NA |
Top 15 diseases |
32118415 |
J Chem Inf Model |
2020 |
| 8 |
83.8 |
893 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
HNet-DNN |
Deep Neural Network (DNN) |
Drug Disease Association (DDA) |
https://github.com/hliu2016/HNet-DNN |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 15 drugs |
32118415 |
J Chem Inf Model |
2020 |
| 8 |
83.8 |
893 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
HNet-DNN |
Deep Neural Network (DNN) |
Drug Disease Association (DDA) |
https://github.com/hliu2016/HNet-DNN |
Case studies |
NA |
NA |
Enalapril |
NA |
Top 15 diseases |
32118415 |
J Chem Inf Model |
2020 |
| 9 |
83 |
1613 |
NA |
Drug, Disease |
Drug: Chemical substructures, the target domains and the gene ontology annotations of target target, Disease: MeSH |
CTST |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Metoprolol |
NA |
Top 10 diseases |
34850815 |
Brief Bioinform |
2022 |
| 9 |
83 |
1613 |
NA |
Drug, Disease |
Drug: Chemical substructures, the target domains and the gene ontology annotations of target target, Disease: MeSH |
CTST |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Propranolol |
NA |
Top 10 diseases |
34850815 |
Brief Bioinform |
2022 |
| 9 |
83 |
1613 |
NA |
Drug, Disease |
Drug: Chemical substructures, the target domains and the gene ontology annotations of target target, Disease: MeSH |
CTST |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Aripiprazole |
NA |
Top 10 diseases |
34850815 |
Brief Bioinform |
2022 |
| 9 |
83 |
1613 |
NA |
Drug, Disease |
Drug: Chemical substructures, the target domains and the gene ontology annotations of target target, Disease: MeSH |
CTST |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Chloroquine |
NA |
Top 10 diseases |
34850815 |
Brief Bioinform |
2022 |
| 9 |
83 |
1613 |
NA |
Drug, Disease |
Drug: Chemical substructures, the target domains and the gene ontology annotations of target target, Disease: MeSH |
CTST |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Flurbiprofen |
NA |
Top 10 diseases |
34850815 |
Brief Bioinform |
2022 |
| 10 |
82.7 |
1848 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 10 diseases |
36182762 |
Comput Biol Med |
2022 |
| 10 |
82.7 |
1848 |
NA |
Drug, Disease, Target, Gene, Pathway |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 10 diseases |
36182762 |
Comput Biol Med |
2022 |
| 10 |
82.7 |
1848 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
NA |
NA |
Ifosfamide |
NA |
Top 10 diseases |
36182762 |
Comput Biol Med |
2022 |
| 10 |
82.7 |
1848 |
NA |
Drug, Disease, Target, Gene, Pathway |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
NA |
NA |
Ifosfamide |
NA |
Top 10 diseases |
36182762 |
Comput Biol Med |
2022 |
| 10 |
82.7 |
1848 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 10 drugs |
36182762 |
Comput Biol Med |
2022 |
| 10 |
82.7 |
1848 |
NA |
Drug, Disease, Target, Gene, Pathway |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 10 drugs |
36182762 |
Comput Biol Med |
2022 |
| 10 |
82.7 |
1848 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
Brain neoplasms |
NA |
NA |
NA |
Top 10 drugs |
36182762 |
Comput Biol Med |
2022 |
| 10 |
82.7 |
1848 |
NA |
Drug, Disease, Target, Gene, Pathway |
Drug: SMILES, Disease: MeSH |
REDDA (Relations-Enhanced Drug-Disease Association prediction) |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Disease Association (DDA) |
https://github.com/gu-yaowen/REDDA |
Case studies |
Brain neoplasms |
NA |
NA |
NA |
Top 10 drugs |
36182762 |
Comput Biol Med |
2022 |
| 11 |
82.1 |
1842 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
PSGCN (Partner-specific drug repositioning approach based on graph convolutional network) |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/PSGCN |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 10 drugs |
35921345 |
IEEE J Biomed Health Inform |
2022 |
| 11 |
82.1 |
1842 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
PSGCN (Partner-specific drug repositioning approach based on graph convolutional network) |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/PSGCN |
Case studies |
Breast Cancer |
NA |
NA |
NA |
Top 10 drugs |
35921345 |
IEEE J Biomed Health Inform |
2022 |
| 11 |
82.1 |
1842 |
Gdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
PSGCN (Partner-specific drug repositioning approach based on graph convolutional network) |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/PSGCN |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 10 drugs |
35921345 |
IEEE J Biomed Health Inform |
2022 |
| 11 |
82.1 |
1842 |
LRSSL |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
PSGCN (Partner-specific drug repositioning approach based on graph convolutional network) |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/PSGCN |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 10 drugs |
35921345 |
IEEE J Biomed Health Inform |
2022 |
| 11 |
82.1 |
1842 |
LRSSL |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
PSGCN (Partner-specific drug repositioning approach based on graph convolutional network) |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/PSGCN |
Case studies |
Breast Cancer |
NA |
NA |
NA |
Top 10 drugs |
35921345 |
IEEE J Biomed Health Inform |
2022 |
| 11 |
82.1 |
1842 |
Gdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
PSGCN (Partner-specific drug repositioning approach based on graph convolutional network) |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/PSGCN |
Case studies |
Breast Cancer |
NA |
NA |
NA |
Top 10 drugs |
35921345 |
IEEE J Biomed Health Inform |
2022 |
| 12 |
81.9 |
2175 |
LRSSL |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
DNdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Fenoldopam |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
2175 |
Gdataset (Fdataset) |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
Fdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Indomethacin |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
2175 |
Ldataset |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
DNdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Diltiazem |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
2175 |
Cdataset |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
Cdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Fenoldopam |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
2175 |
Ldataset |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
DNdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Indomethacin |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
2175 |
Cdataset |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
Cdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Diltiazem |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
1643 |
Fdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Fenoldopam |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
2175 |
Gdataset (Fdataset) |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
Fdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Diltiazem |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 12 |
81.9 |
2175 |
LRSSL |
Drug, Disease |
Drug: 2D chemical fingerprints, Diseases: The semantic similarity of disease phenotypes |
AdaDR (Adaptive Graph Convolutional Networks for Drug Repositioning) |
Adaptive Graph Convolutional Network (AGCN) |
Drug Disease Association (DDA) |
https://github.com/xinliangSun/AdaDR |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 5 drugs |
38070161 |
Bioinformatics |
2024 |
| 12 |
81.9 |
1643 |
Cdataset |
Drug, Disease |
Drug: Hashed fingerprints, Disease: MeSH |
springD²A |
Encoder,Neural networks |
Drug Disease Association (DDA) |
https://github.com/wangyuanhao/springD2A |
Case studies |
NA |
NA |
Indomethacin |
NA |
Top 10 diseases |
34864881 |
Bioinformatics |
2022 |
| 13 |
81.88 |
1407 |
Fdataset |
Drug, Disease |
Drug: SMILES, ATC, side-effect; Disease: the medical subject headings vocabulary, DO. |
MSBMF |
Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MSBMF |
Case studies |
NA |
NA |
Vincristine |
NA |
Top 10 diseases |
33147616 |
Brief Bioinform |
2021 |
| 13 |
81.88 |
1407 |
Fdataset |
Drug, Disease |
Drug: SMILES, ATC, side-effect; Disease: the medical subject headings vocabulary, DO. |
MSBMF |
Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MSBMF |
Case studies |
NA |
NA |
Methotrexate |
NA |
Top 10 diseases |
33147616 |
Brief Bioinform |
2021 |
| 13 |
81.88 |
1407 |
Fdataset |
Drug, Disease |
Drug: SMILES, ATC, side-effect; Disease: the medical subject headings vocabulary, DO. |
MSBMF |
Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MSBMF |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 10 diseases |
33147616 |
Brief Bioinform |
2021 |
| 13 |
81.88 |
1407 |
Fdataset |
Drug, Disease |
Drug: SMILES, ATC, side-effect; Disease: the medical subject headings vocabulary, DO. |
MSBMF |
Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MSBMF |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 10 diseases |
33147616 |
Brief Bioinform |
2021 |
| 13 |
81.88 |
1407 |
Fdataset |
Drug, Disease |
Drug: SMILES, ATC, side-effect; Disease: the medical subject headings vocabulary, DO. |
MSBMF |
Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MSBMF |
Case studies |
NA |
NA |
Gemcitabine |
NA |
Top 10 diseases |
33147616 |
Brief Bioinform |
2021 |
| 14 |
81.8 |
795 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
SKCNN |
Sigmoid Kernel and Convolutional Neural Network (SKCNN),Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/SKCNN |
Case studies |
Asthma |
NA |
NA |
NA |
Top 20 drugs |
31747915 |
J Transl Med |
2019 |
| 14 |
81.8 |
795 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
SKCNN |
Sigmoid Kernel and Convolutional Neural Network (SKCNN),Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/SKCNN |
Case studies |
Obesity |
NA |
NA |
NA |
Top 20 drugs |
31747915 |
J Transl Med |
2019 |
| 14 |
81.8 |
795 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
SKCNN |
Sigmoid Kernel and Convolutional Neural Network (SKCNN),Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/SKCNN |
Case studies |
Asthma |
NA |
NA |
NA |
Top 20 drugs |
31747915 |
J Transl Med |
2019 |
| 14 |
81.8 |
795 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
SKCNN |
Sigmoid Kernel and Convolutional Neural Network (SKCNN),Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/SKCNN |
Case studies |
Obesity |
NA |
NA |
NA |
Top 20 drugs |
31747915 |
J Transl Med |
2019 |
| 15 |
81.7 |
2036 |
DTPKS |
Drug, Target |
Drug: 2D molecular graphs Target: amino acid sequences (AAS) |
MDTips |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/XiaoqiongXia/MDTips |
Case studies |
NA |
NA |
Melphalan |
NA |
Top 30 diseases |
37379157 |
Bioinformatics |
2023 |
| 16 |
81.4 |
1860 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
T2 |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
NA |
NA |
Felodipine |
NA |
Top 5 diseases |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
T1 |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1718 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
MLMC |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MLMC |
Case studies |
NA |
NA |
Gemcitabine |
NA |
Top 5 diseases |
35289352 |
Brief Bioinform |
2022 |
| 16 |
81.4 |
1718 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
MLMC |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MLMC |
Case studies |
NA |
NA |
Methotrexate |
NA |
Top 5 diseases |
35289352 |
Brief Bioinform |
2022 |
| 16 |
81.4 |
1860 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
T1 |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
NA |
NA |
Felodipine |
NA |
Top 5 diseases |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1718 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
MLMC |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MLMC |
Case studies |
NA |
NA |
Leucovorin |
NA |
Top 5 diseases |
35289352 |
Brief Bioinform |
2022 |
| 16 |
81.4 |
1860 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
NA |
NA |
Felodipine |
NA |
Top 5 diseases |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
T2 |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
T2 |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1860 |
T1 |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 10 drugs |
36359016 |
Biomolecules |
2022 |
| 16 |
81.4 |
1718 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
MLMC |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/MLMC |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
35289352 |
Brief Bioinform |
2022 |
| 16 |
81.4 |
1860 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
EMPHCN (Enhanced Message Passing and Hypergraph Convolutional Networks) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/hwh7301/EMPHCN |
Case studies |
NA |
NA |
Felodipine |
NA |
Top 5 diseases |
36359016 |
Biomolecules |
2022 |
| 17 |
81 |
2099 |
NA |
Drug, Disease, Target, Side-effect |
Drug: SMILES, Target: the amino acid sequences |
MOVE |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/scu-kdde/Bioinfo-MOVE2.0 |
Case studies |
COVID-19 |
Peroxisome proliferator-activated receptor gamma(P37231), Peroxisome proliferator-activated receptor alpha(Q07869), Apoptosis regulator Bcl-2(P10415), Angiotensin-converting enzyme 2(Q9BYF1), Cystic fibrosis transmembrane conductance regulator(P13569), Nuclear receptor subfamily 1 group I member 2(O75469), Annexin A1(P04083) |
NA |
NA |
Top 7 drugs |
37586602 |
Methods |
2023 |
| 18 |
80.7 |
1994 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MSGNN-DTA |
Graph Neural Network (GNN) |
Drug Target binding Affinity (DTA) |
https://github.com/songxuanmo/MSGNN-DTA |
Case studies |
NA |
Epidermal Growth Factor Receptor (EGFR) |
NA |
NA |
Top 11 drugs |
37176031 |
Int J Mol Sci |
2023 |
| 18 |
80.7 |
1994 |
KIBA |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MSGNN-DTA |
Graph Neural Network (GNN) |
Drug Target binding Affinity (DTA) |
https://github.com/songxuanmo/MSGNN-DTA |
Case studies |
NA |
Epidermal Growth Factor Receptor (EGFR) |
NA |
NA |
Top 11 drugs |
37176031 |
Int J Mol Sci |
2023 |
| 19 |
80.6 |
895 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Ziprasidone |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Ziprasidone |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
Cdataset |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Fluconazole |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
Cdataset |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Citalopram |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
Cdataset |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Imatinib |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
2071 |
DTINet |
Drug, Disease, Target, Side-effect |
Drug: SMILES, Target: the amino acid sequences |
SHGCL-DTI |
Heterogeneous Graph Convolutional Network (HGCN) |
Drug Target Interaction (DTI) |
https://github.com/TOJSSE-iData/SHGCL-DTI |
Case studies |
NA |
ADRA1B, CHRM1, CHRM2, CHRM3, HTR1A, HTR2B, HTR2C, GABRA4, OPRD1, SLC6A4 |
NA |
NA |
Top 20 drugs |
37421738 |
Comput Biol Med |
2023 |
| 19 |
80.6 |
895 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Warfarin |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Chloroquine |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Warfarin |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Chloroquine |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
Cdataset |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Ziprasidone |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Fluconazole |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Citalopram |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Fluconazole |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Citalopram |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Imatinib |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
Cdataset |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Warfarin |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
Cdataset |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Chloroquine |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 19 |
80.6 |
895 |
PREDICT (Fdataset) |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
DRIMC (Drug repositioning approach by using Bayesian inductive matrix completion) |
Bayesian inductive matrix |
Drug Disease Association (DDA) |
https://github.com/linwang1982/DRIMC |
Case studies |
NA |
NA |
Imatinib |
NA |
Top 5 diseases |
31999326 |
Bioinformatics |
2020 |
| 20 |
80.5 |
393 |
NA |
Drug, Disease, Target , Side-effect |
Drug: chmical structure, Target: genome sequences |
DTINet |
Random Walk with Restart (RWR) |
Drug Target Interaction (DTI) |
https://github.com/luoyunan/DTINet |
Case studies |
NA |
COX proteins |
NA |
NA |
3 drugs |
28924171 |
Nat Commun |
2017 |
| 21 |
80.4 |
1670 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRWBNCF |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/DRWBNCF |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
35039838 |
Brief Bioinform |
2022 |
| 21 |
80.4 |
1670 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRWBNCF |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/DRWBNCF |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 10 drugs |
35039838 |
Brief Bioinform |
2022 |
| 21 |
80.4 |
1670 |
LRSSL |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRWBNCF |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/DRWBNCF |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
35039838 |
Brief Bioinform |
2022 |
| 21 |
80.4 |
1670 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRWBNCF |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/DRWBNCF |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
35039838 |
Brief Bioinform |
2022 |
| 21 |
80.4 |
1670 |
LRSSL |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRWBNCF |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/DRWBNCF |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 10 drugs |
35039838 |
Brief Bioinform |
2022 |
| 21 |
80.4 |
1670 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
DRWBNCF |
Graph Convolutional Network (GCN),Multi Layer Perceptron (MLP) |
Drug Disease Association (DDA) |
https://github.com/luckymengmeng/DRWBNCF |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 10 drugs |
35039838 |
Brief Bioinform |
2022 |
| 22 |
80.3 |
1892 |
DrugBank |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:775 (calcium voltage-gated channel subunit alpha1 C) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_NR |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
NA |
Nisoldipine |
NA |
Top 20 targets |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:779 (calcium voltage-gated channel subunit alpha1 S) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_E |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:775 (calcium voltage-gated channel subunit alpha1 C) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
HGBI |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:779 (calcium voltage-gated channel subunit alpha1 S) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
DrugBank |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:779 (calcium voltage-gated channel subunit alpha1 S) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_NR |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:775 (calcium voltage-gated channel subunit alpha1 C) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_IC |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
NA |
Nisoldipine |
NA |
Top 20 targets |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_E |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:779 (calcium voltage-gated channel subunit alpha1 S) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
NA |
Nisoldipine |
NA |
Top 20 targets |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
HGBI |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
NA |
Nisoldipine |
NA |
Top 20 targets |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_NR |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:779 (calcium voltage-gated channel subunit alpha1 S) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_IC |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:775 (calcium voltage-gated channel subunit alpha1 C) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_IC |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:779 (calcium voltage-gated channel subunit alpha1 S) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:775 (calcium voltage-gated channel subunit alpha1 C) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
Yamanishi_E |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
NA |
Nisoldipine |
NA |
Top 20 targets |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
HGBI |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
hsa:775 (calcium voltage-gated channel subunit alpha1 C) |
NA |
NA |
Top 20 drugs |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 22 |
80.3 |
1892 |
DrugBank |
Drug, Target |
Drug: chemical structure information, Target: target sequence |
PPAEDTI |
Deep Autoencoder |
Drug Target Interaction (DTI) |
https://github.com/LiYuechao1998/PPAEDTI |
Case studies |
NA |
NA |
Nisoldipine |
NA |
Top 20 targets |
36301791 |
IEEE J Biomed Health Inform |
2023 |
| 23 |
79.8 |
486 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Paclitaxel |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Paclitaxel |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Paclitaxel |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Zoledronic acid |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Zoledronic acid |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Zoledronic acid |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
DNdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Prednisolone |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Prednisolone |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 23 |
79.8 |
486 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
DRRS (Drug Repositioning Recommendation System) |
Singular Value Thresholding (SVT) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Prednisolone |
NA |
Top 5 diseases |
29365057 |
Bioinformatics |
2018 |
| 24 |
79.71428571 |
687 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Irinotecan |
NA |
Top 1 drug |
31138103 |
BMC Bioinformatics |
2019 |
| 24 |
79.71428571 |
687 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Cortisol |
NA |
Top 2 drugs |
31138103 |
BMC Bioinformatics |
2019 |
| 24 |
79.71428571 |
687 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Salicylic acid |
NA |
Top 1 drug |
31138103 |
BMC Bioinformatics |
2019 |
| 24 |
79.71428571 |
687 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Ephedrine |
NA |
Top 2 drugs |
31138103 |
BMC Bioinformatics |
2019 |
| 24 |
79.71428571 |
687 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Podophyllotoxin |
NA |
Top 1 drug |
31138103 |
BMC Bioinformatics |
2019 |
| 24 |
79.71428571 |
687 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Testosterone |
NA |
Top 3 drugs |
31138103 |
BMC Bioinformatics |
2019 |
| 24 |
79.71428571 |
687 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
(-)-Prostaglandin E1 |
NA |
Top 1 drug |
31138103 |
BMC Bioinformatics |
2019 |
| 25 |
79.3 |
2179 |
Cdataset |
Drug, Disease, Target |
Drug: SMILES, Target: Sequence, Disease: MesH |
SiSGC (Simplifying Graph Convolution) |
CatBoost |
Drug Disease Association (DDA) |
https://github.com/MrPhil/SiSGC |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 20 drugs |
38103039 |
J Chem Inf Model |
2024 |
| 25 |
79.3 |
2179 |
Fdataset |
Drug, Disease, Target |
Drug: SMILES, Target: Sequence, Disease: MesH |
SiSGC (Simplifying Graph Convolution) |
CatBoost |
Drug Disease Association (DDA) |
https://github.com/MrPhil/SiSGC |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 20 drugs |
38103039 |
J Chem Inf Model |
2024 |
| 25 |
79.3 |
2179 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Target: Sequence, Disease: MesH |
SiSGC (Simplifying Graph Convolution) |
CatBoost |
Drug Disease Association (DDA) |
https://github.com/MrPhil/SiSGC |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 20 drugs |
38103039 |
J Chem Inf Model |
2024 |
| 26 |
78.3 |
1615 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
HINGRL |
Random Forest (RF) |
Drug Disease Association (DDA) |
https://github.com/stevejobws/HINGRL |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 10 drugs |
34891172 |
Brief Bioinform |
2022 |
| 26 |
78.3 |
1615 |
NA |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
HINGRL |
Random Forest (RF) |
Drug Disease Association (DDA) |
https://github.com/stevejobws/HINGRL |
Case studies |
NA |
Clozapine |
NA |
NA |
Top 10 diseases |
34891172 |
Brief Bioinform |
2022 |
| 26 |
78.3 |
1615 |
NA |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH |
HINGRL |
Random Forest (RF) |
Drug Disease Association (DDA) |
https://github.com/stevejobws/HINGRL |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 10 drugs |
34891172 |
Brief Bioinform |
2022 |
| 26 |
78.3 |
1615 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: MeSH |
HINGRL |
Random Forest (RF) |
Drug Disease Association (DDA) |
https://github.com/stevejobws/HINGRL |
Case studies |
NA |
Clozapine |
NA |
NA |
Top 10 diseases |
34891172 |
Brief Bioinform |
2022 |
| 27 |
78.1 |
2203 |
Cdataset |
Drug, Disease |
Chemical, Pharmacological, Therapeutic, Phenotypic, Genetic, Environment properties |
WMAGT |
Graph Convolutional Network,Graph Transformer,Neural Collaborative Filtering,Multilayer Perceptron |
Drug Disease Association (DDA) |
https://github.com/ShiHHe/WMAGT |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
38378479 |
BMC Bioinformatics |
2024 |
| 27 |
78.1 |
2203 |
LRSSL |
Drug, Disease |
Chemical, Pharmacological, Therapeutic, Phenotypic, Genetic, Environment properties |
WMAGT |
Graph Convolutional Network,Graph Transformer,Neural Collaborative Filtering,Multilayer Perceptron |
Drug Disease Association (DDA) |
https://github.com/ShiHHe/WMAGT |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
38378479 |
BMC Bioinformatics |
2024 |
| 27 |
78.1 |
2203 |
Fdataset |
Drug, Disease |
Chemical, Pharmacological, Therapeutic, Phenotypic, Genetic, Environment properties |
WMAGT |
Graph Convolutional Network,Graph Transformer,Neural Collaborative Filtering,Multilayer Perceptron |
Drug Disease Association (DDA) |
https://github.com/ShiHHe/WMAGT |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
38378479 |
BMC Bioinformatics |
2024 |
| 28 |
78 |
1644 |
TL-HBGI |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
NMF-DR (Non-negative Matrix Factorization Drug Repurposing) |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/sshaghayeghs/NMF-DR |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 5 drugs |
34875000 |
Bioinformatics |
2022 |
| 28 |
78 |
1644 |
DrugNet |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
NMF-DR (Non-negative Matrix Factorization Drug Repurposing) |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/sshaghayeghs/NMF-DR |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 5 drugs |
34875000 |
Bioinformatics |
2022 |
| 28 |
78 |
1644 |
Cdataset |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
NMF-DR (Non-negative Matrix Factorization Drug Repurposing) |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/sshaghayeghs/NMF-DR |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 5 drugs |
34875000 |
Bioinformatics |
2022 |
| 28 |
78 |
1644 |
Fdataset |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
NMF-DR (Non-negative Matrix Factorization Drug Repurposing) |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/sshaghayeghs/NMF-DR |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 5 drugs |
34875000 |
Bioinformatics |
2022 |
| 29 |
77.875 |
509 |
LRSSL |
Drug, Disease |
Drug: substructures, Disease: MeSH |
NTSIM (Network Topological Similarity-based Inference Method) |
Label Propagation |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 10 diseases |
29879508 |
Methods |
2018 |
| 29 |
77.875 |
2079 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 29 |
77.875 |
509 |
NA |
Drug, Disease |
Drug: substructures, Disease: MeSH |
NTSIM (Network Topological Similarity-based Inference Method) |
Label Propagation |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 10 diseases |
29879508 |
Methods |
2018 |
| 29 |
77.875 |
2079 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 29 |
77.875 |
2079 |
DrugBank (version 5.1.9) |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 29 |
77.875 |
509 |
Fdataset |
Drug, Disease |
Drug: substructures, Disease: MeSH |
NTSIM (Network Topological Similarity-based Inference Method) |
Label Propagation |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 10 diseases |
29879508 |
Methods |
2018 |
| 29 |
77.875 |
2079 |
KIBA |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 29 |
77.875 |
509 |
TL-HGBI |
Drug, Target |
Drug: substructures, Disease: MeSH |
NTSIM (Network Topological Similarity-based Inference Method) |
Label Propagation |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 10 diseases |
29879508 |
Methods |
2018 |
| 30 |
77.76 |
766 |
LRSSL |
Drug, Disease, Side-effect |
Drug: chemical substructure, domains of target target, GO terms of drug target, Disease associated with the interested Drug, Drug side-effect; Disease: MeSH, Disease ontology |
DisDrugPred |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/pingxuan-hlju/DisDrugPred |
Case studies |
NA |
NA |
Etoposide |
NA |
Top 10 diseases |
30865257 |
Bioinformatics |
2019 |
| 30 |
77.76 |
766 |
LRSSL |
Drug, Disease, Side-effect |
Drug: chemical substructure, domains of target target, GO terms of drug target, Disease associated with the interested Drug, Drug side-effect; Disease: MeSH, Disease ontology |
DisDrugPred |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/pingxuan-hlju/DisDrugPred |
Case studies |
NA |
NA |
Cefotaxime |
NA |
Top 10 diseases |
30865257 |
Bioinformatics |
2019 |
| 30 |
77.76 |
766 |
LRSSL |
Drug, Disease, Side-effect |
Drug: chemical substructure, domains of target target, GO terms of drug target, Disease associated with the interested Drug, Drug side-effect; Disease: MeSH, Disease ontology |
DisDrugPred |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/pingxuan-hlju/DisDrugPred |
Case studies |
NA |
NA |
Ciprofloxacin |
NA |
Top 10 diseases |
30865257 |
Bioinformatics |
2019 |
| 30 |
77.76 |
766 |
LRSSL |
Drug, Disease, Side-effect |
Drug: chemical substructure, domains of target target, GO terms of drug target, Disease associated with the interested Drug, Drug side-effect; Disease: MeSH, Disease ontology |
DisDrugPred |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/pingxuan-hlju/DisDrugPred |
Case studies |
NA |
NA |
Clonidine |
NA |
Top 10 diseases |
30865257 |
Bioinformatics |
2019 |
| 30 |
77.76 |
766 |
LRSSL |
Drug, Disease, Side-effect |
Drug: chemical substructure, domains of target target, GO terms of drug target, Disease associated with the interested Drug, Drug side-effect; Disease: MeSH, Disease ontology |
DisDrugPred |
Non-negative Matrix Factorization (NMF) |
Drug Disease Association (DDA) |
https://github.com/pingxuan-hlju/DisDrugPred |
Case studies |
NA |
NA |
Ampicillin |
NA |
Top 10 diseases |
30865257 |
Bioinformatics |
2019 |
| 31 |
77.7 |
2133 |
Cdataset |
Drug, Disease |
NA |
DRAGNN |
Multi Layer Perception (MLP) |
Drug Disease Association (DDA) |
https://github.com/1yiw/DRAGNN |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
38019732 |
Brief Bioinform |
2023 |
| 31 |
77.7 |
2133 |
LRSSL |
Drug, Disease |
NA |
DRAGNN |
Multi Layer Perception (MLP) |
Drug Disease Association (DDA) |
https://github.com/1yiw/DRAGNN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
38019732 |
Brief Bioinform |
2023 |
| 31 |
77.7 |
2133 |
Fdataset |
Drug, Disease |
NA |
DRAGNN |
Multi Layer Perception (MLP) |
Drug Disease Association (DDA) |
https://github.com/1yiw/DRAGNN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
38019732 |
Brief Bioinform |
2023 |
| 31 |
77.7 |
2133 |
LRSSL |
Drug, Disease |
NA |
DRAGNN |
Multi Layer Perception (MLP) |
Drug Disease Association (DDA) |
https://github.com/1yiw/DRAGNN |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
38019732 |
Brief Bioinform |
2023 |
| 31 |
77.7 |
2133 |
Fdataset |
Drug, Disease |
NA |
DRAGNN |
Multi Layer Perception (MLP) |
Drug Disease Association (DDA) |
https://github.com/1yiw/DRAGNN |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
38019732 |
Brief Bioinform |
2023 |
| 31 |
77.7 |
2133 |
Cdataset |
Drug, Disease |
NA |
DRAGNN |
Multi Layer Perception (MLP) |
Drug Disease Association (DDA) |
https://github.com/1yiw/DRAGNN |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
38019732 |
Brief Bioinform |
2023 |
| 32 |
77.35 |
1367 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: Phenotype |
DDIPred |
Deep gated recurrent units model |
Drug Disease Association (DDA) |
https://github.com/haichengyi/DDIPre |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 15 diseases |
34074242 |
BMC Bioinformatics |
2021 |
| 32 |
77.35 |
1367 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: Phenotype |
DDIPred |
Deep gated recurrent units model |
Drug Disease Association (DDA) |
https://github.com/haichengyi/DDIPre |
Case studies |
NA |
NA |
Zoledronic acid |
NA |
Top 10 diseases |
34074242 |
BMC Bioinformatics |
2021 |
| 32 |
77.35 |
1367 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: Phenotype |
DDIPred |
Deep gated recurrent units model |
Drug Disease Association (DDA) |
https://github.com/haichengyi/DDIPre |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 15 diseases |
34074242 |
BMC Bioinformatics |
2021 |
| 32 |
77.35 |
1367 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: Phenotype |
DDIPred |
Deep gated recurrent units model |
Drug Disease Association (DDA) |
https://github.com/haichengyi/DDIPre |
Case studies |
NA |
NA |
Zoledronic acid |
NA |
Top 10 diseases |
34074242 |
BMC Bioinformatics |
2021 |
| 33 |
77.3 |
957 |
NA |
Drug, Disease, Target |
NA |
BiFusion (Bipartite graph convolution network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/zcwang0702/BiFusion |
Case studies |
Breast carcinoma |
NA |
NA |
NA |
Top 5 drugs |
32657387 |
Bioinformatics |
2020 |
| 33 |
77.3 |
957 |
NA |
Drug, Disease, Target |
NA |
BiFusion (Bipartite graph convolution network) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
https://github.com/zcwang0702/BiFusion |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 10 drugs |
32657387 |
Bioinformatics |
2020 |
| 34 |
77.25 |
739 |
Fdataset |
Drug, Disease |
Drug: Fingerprint, Diseases: MeSH terms |
GIPAE (Gaussian interaction profile kernel and autoencoder) |
Deep Autoencoder,Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/GIPAE |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 20 drug |
31534955 |
Biomed Res Int |
2019 |
| 34 |
77.25 |
739 |
Cdataset |
Drug, Disease |
Drug: Fingerprint, Diseases: MeSH terms |
GIPAE (Gaussian interaction profile kernel and autoencoder) |
Deep Autoencoder,Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/GIPAE |
Case studies |
Obesity |
NA |
NA |
NA |
Top 20 drug |
31534955 |
Biomed Res Int |
2019 |
| 34 |
77.25 |
739 |
Cdataset |
Drug, Disease |
Drug: Fingerprint, Diseases: MeSH terms |
GIPAE (Gaussian interaction profile kernel and autoencoder) |
Deep Autoencoder,Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/GIPAE |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 20 drug |
31534955 |
Biomed Res Int |
2019 |
| 34 |
77.25 |
739 |
Fdataset |
Drug, Disease |
Drug: Fingerprint, Diseases: MeSH terms |
GIPAE (Gaussian interaction profile kernel and autoencoder) |
Deep Autoencoder,Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
https://github.com/HanJingJiang/GIPAE |
Case studies |
Obesity |
NA |
NA |
NA |
Top 20 drug |
31534955 |
Biomed Res Int |
2019 |
| 35 |
77.2 |
949 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence data in FASTA format Disease: MeSH |
TS-SVD |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
Non-Small Cell Lung Cancer (NSCLC) |
NA |
NA |
NA |
Top 10 drugs |
32340956 |
IEEE Trans Nanobioscience |
2020 |
| 36 |
76.8 |
1532 |
Fdataset |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
LMFDA |
Inductive matrix |
Drug Disease Association (DDA) |
https://github.com/hupengwei/LMFDA_Dataset |
Case studies |
Ischemic stroke |
NA |
NA |
NA |
Top 10 drugs |
34736437 |
BMC Med Inform Decis Mak |
2021 |
| 36 |
76.8 |
720 |
DNdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
Cdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
Cdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
1532 |
Cdataset |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
LMFDA |
Inductive matrix |
Drug Disease Association (DDA) |
https://github.com/hupengwei/LMFDA_Dataset |
Case studies |
Type 2 Diabetes Mellitus (T2DM) |
NA |
NA |
NA |
Top 10 drugs |
34736437 |
BMC Med Inform Decis Mak |
2021 |
| 36 |
76.8 |
720 |
Cdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
DNdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Levodopa |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
1532 |
Cdataset |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
LMFDA |
Inductive matrix |
Drug Disease Association (DDA) |
https://github.com/hupengwei/LMFDA_Dataset |
Case studies |
Ischemic stroke |
NA |
NA |
NA |
Top 10 drugs |
34736437 |
BMC Med Inform Decis Mak |
2021 |
| 36 |
76.8 |
720 |
Cdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
DNdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Doxorubicin |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
DNdataset |
Drug, Disease |
NA |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Amantadine |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
720 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
BNNR (Bounded Nuclear Norm Regularization) |
Matrix Completion |
Drug Disease Association (DDA) |
https://github.com/BioinformaticsCSU/BNNR |
Case studies |
NA |
NA |
Flecainide |
NA |
Top 5 diseases |
31510658 |
Bioinformatics |
2019 |
| 36 |
76.8 |
1532 |
Fdataset |
Drug, Disease |
Drug: Chemical structure, Disease: MeSH |
LMFDA |
Inductive matrix |
Drug Disease Association (DDA) |
https://github.com/hupengwei/LMFDA_Dataset |
Case studies |
Type 2 Diabetes Mellitus (T2DM) |
NA |
NA |
NA |
Top 10 drugs |
34736437 |
BMC Med Inform Decis Mak |
2021 |
| 37 |
76.54 |
1197 |
SND |
Drug, Disease |
NA |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Loteprednol |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
Fdataset |
Drug, Disease |
Drug: SMILES; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Sparfloxacin |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
SND |
Drug, Disease |
NA |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Triamcinolone |
NA |
Top 6 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
Fdataset |
Drug, Disease |
Drug: SMILES; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
SND |
Drug, Disease |
NA |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Levofloxacin |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Sparfloxacin |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
Fdataset |
Drug, Disease |
Drug: SMILES; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Triamcinolone |
NA |
Top 6 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
Fdataset |
Drug, Disease |
Drug: SMILES; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Levofloxacin |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
SND |
Drug, Disease |
NA |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Loteprednol |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Triamcinolone |
NA |
Top 6 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Dexamethasone |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
LRSSL |
Drug, Disease |
Drug: drug chemical structure, Pfam domain annotation of drug targets, gene ontology term of targets; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Levofloxacin |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
Fdataset |
Drug, Disease |
Drug: SMILES; Disease: Phenotye |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Loteprednol |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 37 |
76.54 |
1197 |
SND |
Drug, Disease |
NA |
SNF-NN (Similarity network fusion and neural networks) |
Similarity Network Fusion (SNF),Neural Network |
Drug Disease Association (DDA) |
http://pages.cpsc.ucalgary.ca/ tnjarada/snf-nn.php |
Case studies |
NA |
NA |
Sparfloxacin |
NA |
Top 7 diseases |
33482713 |
BMC Bioinformatics |
2021 |
| 38 |
76.425 |
2070 |
RepoDB |
Drug, Disease |
Drug: RDKit fingerprints, Disease: MeSH |
TNA-DR (Tail-Node Augmentation for Drug Repositioning) |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
NA |
Case studies |
Lung neoplasms |
NA |
NA |
NA |
Top 10 drugs |
37418410 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 38 |
76.425 |
2070 |
Fdataset |
Drug, Disease |
Drug: RDKit fingerprints, Disease: MeSH |
TNA-DR (Tail-Node Augmentation for Drug Repositioning) |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
NA |
Case studies |
Lung neoplasms |
NA |
NA |
NA |
Top 10 drugs |
37418410 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 38 |
76.425 |
2070 |
Cdataset |
Drug, Disease |
Drug: RDKit fingerprints, Disease: MeSH |
TNA-DR (Tail-Node Augmentation for Drug Repositioning) |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
NA |
Case studies |
Lung neoplasms |
NA |
NA |
NA |
Top 10 drugs |
37418410 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 38 |
76.425 |
2070 |
LRSSL |
Drug, Disease |
Drug: RDKit fingerprints, Disease: MeSH |
TNA-DR (Tail-Node Augmentation for Drug Repositioning) |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
NA |
Case studies |
Lung neoplasms |
NA |
NA |
NA |
Top 10 drugs |
37418410 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 39 |
76.4 |
1394 |
DTINet |
Drug, Disease, Target, Side-effect |
Drug: structure, Target: sequence |
LUNAR |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
COVID-19 |
ACE2 |
NA |
NA |
Top 8 drugs |
34081583 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 39 |
76.4 |
1394 |
DTINet |
Drug, Disease, Target, Side-effect |
Drug: structure, Target: sequence |
LUNAR |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
COVID-19 |
Tumor necrosis factor |
NA |
NA |
Top 10 drugs |
34081583 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 39 |
76.4 |
1394 |
DTINet |
Drug, Disease, Target, Side-effect |
Drug: structure, Target: sequence |
LUNAR |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
COVID-19 |
Nterleukin-l beta |
NA |
NA |
Top 5 drugs |
34081583 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 40 |
76.3 |
2145 |
Davis |
Drug, Target |
Drug: SMILES, Target: The amino acid Sequence. |
MdDTI |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/lhhu1999/MdDTI |
Case studies |
COVID-19 |
SARS-CoV-2 3C-like protease |
NA |
NA |
Top 5 drugs |
37844375 |
Comput Biol Chem |
2023 |
| 40 |
76.3 |
2145 |
KIBA |
Drug, Target |
Drug: SMILES, Target: The amino acid Sequence. |
MdDTI |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/lhhu1999/MdDTI |
Case studies |
COVID-19 |
SARS-CoV-2 3C-like protease |
NA |
NA |
Top 5 drugs |
37844375 |
Comput Biol Chem |
2023 |
| 41 |
76.1 |
298 |
NA |
Compound, Target |
Compound: SMILES, Target: Sequence |
REMAP |
Dual Regularized One-Class Collaborative Filtering |
Compound Protein Interaction (CPI) |
https://github.com/hansaimlim/REMAP |
Case studies |
Many types of cancer |
NA |
NA |
NA |
Top 7 drugs |
27716836 |
PLoS Comput Biol |
2016 |
| 41 |
76.1 |
1487 |
NA |
Drug, Gene |
NA |
GraphRepur |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://github.com/cckamy/GraphRepur |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 30 drugs |
33739367 |
Bioinformatics |
2021 |
| 42 |
76 |
320 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
TP-NRWRH |
Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
https://github.com/td1799/TP-NRWRH |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
28155639 |
BMC Bioinformatics |
2016 |
| 42 |
76 |
1578 |
NA |
Drug, Target |
Drug: chemical structures, Target: primary sequence |
GANDTI |
Generative Adversarial Network (GAN),Graph convolutional autoencoder |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Ziprasidone |
NA |
Top 10 targets |
32750854 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 42 |
76 |
1578 |
NA |
Drug, Target |
Drug: chemical structures, Target: primary sequence |
GANDTI |
Generative Adversarial Network (GAN),Graph convolutional autoencoder |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Quetiapine |
NA |
Top 10 targets |
32750854 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 42 |
76 |
1578 |
NA |
Drug, Target |
Drug: chemical structures, Target: primary sequence |
GANDTI |
Generative Adversarial Network (GAN),Graph convolutional autoencoder |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Clozapine |
NA |
Top 10 targets |
32750854 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 42 |
76 |
2093 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DGDTA |
Graph Attention Network (GAT),Graph Convolutional Network (GCN),Bidirectional Long Short-Term Memory (Bi-LSTM),Multilayer Convolutional Network |
Drug Target binding Affinity (DTA) |
https://github.com/luojunwei/DGDTA |
Case studies |
NA |
Receptor Tyrosine Kinases (RTKs) |
NA |
NA |
Top 1 drug |
37777712 |
BMC Bioinformatics |
2023 |
| 42 |
76 |
1578 |
NA |
Drug, Target |
Drug: chemical structures, Target: primary sequence |
GANDTI |
Generative Adversarial Network (GAN),Graph convolutional autoencoder |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Olanzapine |
NA |
Top 10 targets |
32750854 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 42 |
76 |
2093 |
KIBA |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DGDTA |
Graph Attention Network (GAT),Graph Convolutional Network (GCN),Bidirectional Long Short-Term Memory (Bi-LSTM),Multilayer Convolutional Network |
Drug Target binding Affinity (DTA) |
https://github.com/luojunwei/DGDTA |
Case studies |
NA |
Receptor Tyrosine Kinases (RTKs) |
NA |
NA |
Top 1 drug |
37777712 |
BMC Bioinformatics |
2023 |
| 42 |
76 |
1578 |
NA |
Drug, Target |
Drug: chemical structures, Target: primary sequence |
GANDTI |
Generative Adversarial Network (GAN),Graph convolutional autoencoder |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Aripiprnazole |
NA |
Top 10 targets |
32750854 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 42 |
76 |
320 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
TP-NRWRH |
Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
https://github.com/td1799/TP-NRWRH |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
28155639 |
BMC Bioinformatics |
2016 |
| 43 |
75.8 |
308 |
Positive dataset |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
dtipred |
Random Forest (RF) |
Drug Target Interaction (DTI) |
http://bioinformatics.ua.pt/software/dtipred/ |
Case studies |
Methicillin-resistant Staphylococcus aureus |
(DNA-directed RNA polymerase subunit alpha_Q5HDY4, 30S ribosomal protein S12_Q5HID0, DNA-directed RNA polymerase subunit beta_Q5HID3, Accessory Sec system protein translocase subunit SecY2_Q5HCP4, 30S ribosomal protein S15_Q5HGF8, Elongation factor G_Q5HIC8, 50S ribosomal protein L22_Q5HDW3, 30S ribosomal protein S3_Q5HDW4, 50S ribosomal protein L13_Q5HDZ0, 50S ribosomal protein L25_Q5HIH4) |
NA |
NA |
Top 5 drugs |
27893735 |
PLoS Comput Biol |
2016 |
| 43 |
75.8 |
308 |
Negative dataset |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
dtipred |
Random Forest (RF) |
Drug Target Interaction (DTI) |
http://bioinformatics.ua.pt/software/dtipred/ |
Case studies |
Methicillin-resistant Staphylococcus aureus |
(DNA-directed RNA polymerase subunit alpha_Q5HDY4, 30S ribosomal protein S12_Q5HID0, DNA-directed RNA polymerase subunit beta_Q5HID3, Accessory Sec system protein translocase subunit SecY2_Q5HCP4, 30S ribosomal protein S15_Q5HGF8, Elongation factor G_Q5HIC8, 50S ribosomal protein L22_Q5HDW3, 30S ribosomal protein S3_Q5HDW4, 50S ribosomal protein L13_Q5HDZ0, 50S ribosomal protein L25_Q5HIH4) |
NA |
NA |
Top 5 drugs |
27893735 |
PLoS Comput Biol |
2016 |
| 44 |
75.6 |
894 |
Validations-ChEMBL |
Drug, Target |
Drug: SMILES, targets: Uniprot ID |
AOPEDF (Arbitrary-Order Proximity Embedded Deep Forest) |
Deep Forest Classifier |
Drug Target Interaction (DTI) |
https://github.com/ChengF-Lab/AOPEDF |
Case studies |
Substance abuse disorder |
G-protein-coupled receptors (GPCRs) |
NA |
NA |
Top 20 drugs |
31971579 |
Bioinformatics |
2020 |
| 44 |
75.6 |
894 |
Training Data-(DrugBank (v4.3), TTD, PharmGKB) |
Drug, Disease, Target , Side-effect |
Drug: SMILES, targets: Uniprot ID |
AOPEDF (Arbitrary-Order Proximity Embedded Deep Forest) |
Deep Forest Classifier |
Drug Target Interaction (DTI) |
https://github.com/ChengF-Lab/AOPEDF |
Case studies |
Substance abuse disorder |
G-protein-coupled receptors (GPCRs) |
NA |
NA |
Top 20 drugs |
31971579 |
Bioinformatics |
2020 |
| 44 |
75.6 |
894 |
Validations-DrugCentral |
Drug, Target |
Drug: SMILES, targets: Uniprot ID |
AOPEDF (Arbitrary-Order Proximity Embedded Deep Forest) |
Deep Forest Classifier |
Drug Target Interaction (DTI) |
https://github.com/ChengF-Lab/AOPEDF |
Case studies |
Substance abuse disorder |
G-protein-coupled receptors (GPCRs) |
NA |
NA |
Top 20 drugs |
31971579 |
Bioinformatics |
2020 |
| 45 |
75 |
2066 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: the medical description information |
SSLDR |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Doxorubicin, Gemcitabine, Vincristine |
NA |
Top 5 diseases |
37028367 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 45 |
75 |
2066 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: the medical description information |
SSLDR |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Doxorubicin, Gemcitabine, Vincristine |
NA |
Top 5 diseases |
37028367 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 45 |
75 |
2066 |
DNdataset |
Drug, Disease |
Drug: SMILES, Disease: the medical description information |
SSLDR |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Doxorubicin, Gemcitabine, Vincristine |
NA |
Top 5 diseases |
37028367 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 46 |
74.9 |
1623 |
NA |
Drug |
Drug: chemical structures, Target: protein sequence |
DOTA (Drug repositioning approach using Optimal Transport for Alzheimer's disease) |
Deep Autoencoder (Multi-modal,Wasserstein variational) |
Drug Disease Association (DDA) |
https://github.com/fawer/DOTA |
Special studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 20 drugs |
35204697 |
Biomolecules |
2022 |
| 47 |
74.3 |
694 |
NA |
Drug, Target |
Drug: Chemical structure, Target: target sequence |
LASSO |
Deep Neural Network (DNN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Breast Cancer |
NA |
NA |
NA |
Top 5 drugs |
30939415 |
Comput Biol Chem |
2019 |
| 48 |
73.9 |
2102 |
DDKG-V1 |
Drug, Disease, Target, Gene |
NA |
DrugRep-HeSiaGraph |
Siamese Neural Network (SNN) |
Drug Disease Association (DDA) |
https://github.com/CBRC-lab/DrugRep-HeSiaGraph |
Case studies |
COVID-19 |
Dipeptidyl Peptidase 4 (DPP-4) |
NA |
NA |
Top 10 drugs |
37789314 |
BMC Bioinformatics |
2023 |
| 49 |
73.7 |
1366 |
NA |
Drug, Target |
Molecular descriptors |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
https://github.com/sblab/DTN |
Special studies |
Hyperlipidemia |
NA |
NA |
NA |
Top 9 drugs |
34030115 |
Comput Biol Chem |
2021 |
| 50 |
73.5 |
1683 |
RPD-Net |
Drug, Disease, Target |
Drug: chemical substructures, Target: the primary sequences |
DNDTI |
Non-negative Matrix Factorization (NMF) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Asenapine |
NA |
Top 10 targets |
34673498 |
IEEE J Biomed Health Inform |
2022 |
| 50 |
73.5 |
1683 |
RPD-Net |
Drug, Disease, Target |
Drug: chemical substructures, Target: the primary sequences |
DNDTI |
Non-negative Matrix Factorization (NMF) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Amitriptyline |
NA |
Top 10 targets |
34673498 |
IEEE J Biomed Health Inform |
2022 |
| 50 |
73.5 |
717 |
LRSSL |
Drug, Disease |
Drug: chemical substructure, chemical fingerprints, Disease: MeSH |
CBPred |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Ceftriaxone |
NA |
Top 10 diseases |
31336774 |
Cells |
2019 |
| 50 |
73.5 |
717 |
LRSSL |
Drug, Disease |
Drug: chemical substructure, chemical fingerprints, Disease: MeSH |
CBPred |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Ofloxacin |
NA |
Top 10 diseases |
31336774 |
Cells |
2019 |
| 50 |
73.5 |
1683 |
RPD-Net |
Drug, Disease, Target |
Drug: chemical substructures, Target: the primary sequences |
DNDTI |
Non-negative Matrix Factorization (NMF) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Clozapine |
NA |
Top 10 targets |
34673498 |
IEEE J Biomed Health Inform |
2022 |
| 50 |
73.5 |
717 |
LRSSL |
Drug, Disease |
Drug: chemical substructure, chemical fingerprints, Disease: MeSH |
CBPred |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Ampicillin |
NA |
Top 10 diseases |
31336774 |
Cells |
2019 |
| 50 |
73.5 |
1683 |
RPD-Net |
Drug, Disease, Target |
Drug: chemical substructures, Target: the primary sequences |
DNDTI |
Non-negative Matrix Factorization (NMF) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Olanzapine |
NA |
Top 10 targets |
34673498 |
IEEE J Biomed Health Inform |
2022 |
| 50 |
73.5 |
1683 |
RPD-Net |
Drug, Disease, Target |
Drug: chemical substructures, Target: the primary sequences |
DNDTI |
Non-negative Matrix Factorization (NMF) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Aripiprazole |
NA |
Top 10 targets |
34673498 |
IEEE J Biomed Health Inform |
2022 |
| 50 |
73.5 |
717 |
LRSSL |
Drug, Disease |
Drug: chemical substructure, chemical fingerprints, Disease: MeSH |
CBPred |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Levofloxacin |
NA |
Top 10 diseases |
31336774 |
Cells |
2019 |
| 50 |
73.5 |
717 |
LRSSL |
Drug, Disease |
Drug: chemical substructure, chemical fingerprints, Disease: MeSH |
CBPred |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Ciprofloxacin |
NA |
Top 10 diseases |
31336774 |
Cells |
2019 |
| 51 |
73.2 |
1981 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
NA |
Fludiazepam |
NA |
Top 20 targets |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 51 |
73.2 |
1981 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
NA |
Fludiazepam |
NA |
Top 20 targets |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 51 |
73.2 |
1981 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
Epidermal Growth Factor Receptor (EGFR) |
NA |
NA |
Top 20 drugs |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 51 |
73.2 |
1981 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
Epidermal Growth Factor Receptor (EGFR) |
NA |
NA |
Top 20 drugs |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 51 |
73.2 |
1981 |
KIBA |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
NA |
Fludiazepam |
NA |
Top 20 targets |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 51 |
73.2 |
1981 |
DrugBank |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
NA |
Fludiazepam |
NA |
Top 20 targets |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 51 |
73.2 |
1981 |
KIBA |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
Epidermal Growth Factor Receptor (EGFR) |
NA |
NA |
Top 20 drugs |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 51 |
73.2 |
1981 |
DrugBank |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GIFDTI |
Convolutional Neural Network (CNN),Transformer |
Drug Target Interaction (DTI) |
https://github.com/zhaoqichang/GIFDTI |
Case studies |
NA |
Epidermal Growth Factor Receptor (EGFR) |
NA |
NA |
Top 20 drugs |
36445997 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 52 |
72.95 |
2134 |
External Set-1 |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 52 |
72.95 |
2134 |
External Set-2 |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 52 |
72.95 |
2134 |
DRH |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 52 |
72.95 |
2134 |
NA |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 53 |
72.6 |
1614 |
DrugBank |
Drug |
Drug: enzymes, side effects, substructures and targets |
GCNMK |
Graph Convolutional Network with multi-kernel (GCNMK) |
Drug Drug Interaction (DDI) |
NA |
Case studies |
Lung neoplasms |
NA |
NA |
NA |
Top 10 drugs |
34864856 |
Brief Bioinform |
2022 |
| 53 |
72.6 |
1614 |
DrugBank |
Drug |
Drug: enzymes, side effects, substructures and targets |
GCNMK |
Graph Convolutional Network with multi-kernel (GCNMK) |
Drug Drug Interaction (DDI) |
NA |
Case studies |
Breast neoplasms |
NA |
NA |
NA |
Top 10 drugs |
34864856 |
Brief Bioinform |
2022 |
| 53 |
72.6 |
1614 |
DrugBank |
Drug |
Drug: enzymes, side effects, substructures and targets |
GCNMK |
Graph Convolutional Network with multi-kernel (GCNMK) |
Drug Drug Interaction (DDI) |
NA |
Case studies |
Colorectal neoplasms |
NA |
NA |
NA |
Top 10 drugs |
34864856 |
Brief Bioinform |
2022 |
| 54 |
72.35 |
812 |
NA |
Drug, Disease, Target , Side-effect |
NA |
deepDR |
Multimodal deep autoencoder (MDA),Collective variational autoencoder (cVAE),Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
https://github.com/ChengF-Lab/deepDR |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 20 drugs |
31116390 |
Bioinformatics |
2019 |
| 54 |
72.35 |
812 |
External validation set |
NA |
NA |
deepDR |
Multimodal deep autoencoder (MDA),Collective variational autoencoder (cVAE),Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
https://github.com/ChengF-Lab/deepDR |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 20 drugs |
31116390 |
Bioinformatics |
2019 |
| 54 |
72.35 |
812 |
External validation set |
NA |
NA |
deepDR |
Multimodal deep autoencoder (MDA),Collective variational autoencoder (cVAE),Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
https://github.com/ChengF-Lab/deepDR |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 20 drugs |
31116390 |
Bioinformatics |
2019 |
| 54 |
72.35 |
812 |
NA |
Drug, Disease, Target , Side-effect |
NA |
deepDR |
Multimodal deep autoencoder (MDA),Collective variational autoencoder (cVAE),Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
https://github.com/ChengF-Lab/deepDR |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 20 drugs |
31116390 |
Bioinformatics |
2019 |
| 55 |
72.3 |
1765 |
Human |
Drug, Target |
Drug: SMILES, Target: binding site |
AttentionSiteDTI |
Bidirectional Long Short-Term Memory (Bi-LSTM),Graph Convolutional Network (GCN),Multi-Layer Perceptron (MLP) |
Drug Target Interaction (DTI) |
https://github.com/yazdanimehdi/AttentionSiteDTI |
Case studies |
COVID-19 |
SARS-CoV-2 |
NA |
NA |
Top 7 drugs |
35817396 |
Brief Bioinform |
2022 |
| 55 |
72.3 |
125 |
NA |
Drug, Disease |
Drug: structure chemical, target, side-effect; Diseases: disease phenotypes, disease ontology, disease genes |
DDR |
Block Coordinate Descent (BCD) |
Drug Disease Association (DDA) |
NA |
Case studies |
Systemic Lupus Erythematosus (SLE) |
NA |
NA |
NA |
Top 10 drugs |
25954437 |
AMIA Annu Symp Proc |
2014 |
| 55 |
72.3 |
1765 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: binding site |
AttentionSiteDTI |
Bidirectional Long Short-Term Memory (Bi-LSTM),Graph Convolutional Network (GCN),Multi-Layer Perceptron (MLP) |
Drug Target Interaction (DTI) |
https://github.com/yazdanimehdi/AttentionSiteDTI |
Case studies |
COVID-19 |
SARS-CoV-2 |
NA |
NA |
Top 7 drugs |
35817396 |
Brief Bioinform |
2022 |
| 55 |
72.3 |
125 |
NA |
Drug, Disease |
Drug: structure chemical, target, side-effect; Diseases: disease phenotypes, disease ontology, disease genes |
DDR |
Block Coordinate Descent (BCD) |
Drug Disease Association (DDA) |
NA |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
25954437 |
AMIA Annu Symp Proc |
2014 |
| 55 |
72.3 |
1765 |
DUD-E |
Drug, Target |
Drug: SMILES, Target: binding site |
AttentionSiteDTI |
Bidirectional Long Short-Term Memory (Bi-LSTM),Graph Convolutional Network (GCN),Multi-Layer Perceptron (MLP) |
Drug Target Interaction (DTI) |
https://github.com/yazdanimehdi/AttentionSiteDTI |
Case studies |
COVID-19 |
SARS-CoV-2 |
NA |
NA |
Top 7 drugs |
35817396 |
Brief Bioinform |
2022 |
| 56 |
72.15 |
2125 |
RepoDB |
Drug, Disease |
NA |
BEHOR |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://zenodo.org/record/8402843 |
Case studies |
Congestive heart failure |
NA |
NA |
NA |
Top 2 drugs |
37925215 |
Artif Intell Med |
2023 |
| 56 |
72.15 |
2125 |
NA |
Drug, Target, Pathway, Phenotype |
NA |
BEHOR |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://zenodo.org/record/8402843 |
Case studies |
Congestive heart failure |
NA |
NA |
NA |
Top 2 drugs |
37925215 |
Artif Intell Med |
2023 |
| 56 |
72.15 |
2125 |
RepoDB |
Drug, Disease |
NA |
BEHOR |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://zenodo.org/record/8402843 |
Case studies |
Rheumatoid arthritis |
NA |
NA |
NA |
Top 2 drugs |
37925215 |
Artif Intell Med |
2023 |
| 56 |
72.15 |
2125 |
RepoDB |
Drug, Disease |
NA |
BEHOR |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://zenodo.org/record/8402843 |
Case studies |
Left ventricular hypertrophy |
NA |
NA |
NA |
Top 1 drug |
37925215 |
Artif Intell Med |
2023 |
| 56 |
72.15 |
2125 |
NA |
Drug, Target, Pathway, Phenotype |
NA |
BEHOR |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://zenodo.org/record/8402843 |
Case studies |
Rheumatoid arthritis |
NA |
NA |
NA |
Top 2 drugs |
37925215 |
Artif Intell Med |
2023 |
| 56 |
72.15 |
2125 |
NA |
Drug, Target, Pathway, Phenotype |
NA |
BEHOR |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://zenodo.org/record/8402843 |
Case studies |
Left ventricular hypertrophy |
NA |
NA |
NA |
Top 1 drug |
37925215 |
Artif Intell Med |
2023 |
| 57 |
72.1 |
2022 |
HetioNet |
Drug, Disease, Gene, Pathway |
Drug: ATC, Disease: MeSH |
DREAMwalk |
Multi-layer random walk |
Drug Disease Association (DDA) |
https://github.com/eugenebang/DREAMwalk |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
37322032 |
Nat Commun |
2023 |
| 57 |
72.1 |
2022 |
KEGG |
Drug, Disease, Gene, Pathway |
Drug: ATC, Disease: MeSH |
DREAMwalk |
Multi-layer random walk |
Drug Disease Association (DDA) |
https://github.com/eugenebang/DREAMwalk |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
37322032 |
Nat Commun |
2023 |
| 57 |
72.1 |
1244 |
NA |
Drug, Disease |
Drug: chemical structural, |
CMLDR |
Collaborative metric learning algorithm |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Risperidone |
NA |
Top 20 diseases |
31283509 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 57 |
72.1 |
2022 |
Multi-scale interactome (MSI) network |
Drug, Disease, Gene |
Drug: ATC, Disease: MeSH |
DREAMwalk |
Multi-layer random walk |
Drug Disease Association (DDA) |
https://github.com/eugenebang/DREAMwalk |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
37322032 |
Nat Commun |
2023 |
| 57 |
72.1 |
2022 |
KEGG |
Drug, Disease, Gene, Pathway |
Drug: ATC, Disease: MeSH |
DREAMwalk |
Multi-layer random walk |
Drug Disease Association (DDA) |
https://github.com/eugenebang/DREAMwalk |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
37322032 |
Nat Commun |
2023 |
| 57 |
72.1 |
1244 |
NA |
Drug, Disease |
Drug: chemical structural, |
CMLDR |
Collaborative metric learning algorithm |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Cyclophosphamide |
NA |
Top 20 diseases |
31283509 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 57 |
72.1 |
2022 |
Multi-scale interactome (MSI) network |
Drug, Disease, Gene |
Drug: ATC, Disease: MeSH |
DREAMwalk |
Multi-layer random walk |
Drug Disease Association (DDA) |
https://github.com/eugenebang/DREAMwalk |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
37322032 |
Nat Commun |
2023 |
| 57 |
72.1 |
2022 |
HetioNet |
Drug, Disease, Gene, Pathway |
Drug: ATC, Disease: MeSH |
DREAMwalk |
Multi-layer random walk |
Drug Disease Association (DDA) |
https://github.com/eugenebang/DREAMwalk |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
37322032 |
Nat Commun |
2023 |
| 58 |
71.75 |
424 |
NA |
Drug, Disease, Gene |
Drug: SMILES, Disease: MeSH |
SSGC (Semi-Supervised Graph Cut) |
Semi-supervised graph cut |
Drug Disease Association (DDA) |
NA |
Case studies |
Non-Small Cell Lung Cancer (NSCLC) |
NA |
NA |
NA |
Top 20 drugs |
29297383 |
BMC Med Genomics |
2017 |
| 58 |
71.75 |
424 |
NA |
Drug, Disease, Gene |
Drug: SMILES, Disease: MeSH |
SSGC (Semi-Supervised Graph Cut) |
Semi-supervised graph cut |
Drug Disease Association (DDA) |
NA |
Case studies |
Alcohol dependence |
NA |
NA |
NA |
Top 20 drugs |
29297383 |
BMC Med Genomics |
2017 |
| 58 |
71.75 |
424 |
NA |
Drug, Disease, Gene |
Drug: SMILES, Disease: MeSH |
SSGC (Semi-Supervised Graph Cut) |
Semi-supervised graph cut |
Drug Disease Association (DDA) |
NA |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 20 drugs |
29297383 |
BMC Med Genomics |
2017 |
| 58 |
71.75 |
424 |
NA |
Drug, Disease, Gene |
Drug: SMILES, Disease: MeSH |
SSGC (Semi-Supervised Graph Cut) |
Semi-supervised graph cut |
Drug Disease Association (DDA) |
NA |
Case studies |
Huntington Disease (HD) |
NA |
NA |
NA |
Top 20 drugs |
29297383 |
BMC Med Genomics |
2017 |
| 59 |
71.7 |
771 |
Fdataset |
Drug, Disease |
Drug: SMILES, Proten: the amino acid sequence, Diseases: MeSH terms |
RWHNDR (Random Walk on a Heterogeneous Network for Drug Repositioning) |
Random Walk |
Drug Disease Association (DDA) |
NA |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 5 drugs |
29994051 |
IEEE/ACM Trans Comput Biol Bioinform |
2019 |
| 59 |
71.7 |
771 |
Fdataset |
Drug, Disease |
Drug: SMILES, Proten: the amino acid sequence, Diseases: MeSH terms |
RWHNDR (Random Walk on a Heterogeneous Network for Drug Repositioning) |
Random Walk |
Drug Disease Association (DDA) |
NA |
Case studies |
Lung cancer |
NA |
NA |
NA |
Top 5 drugs |
29994051 |
IEEE/ACM Trans Comput Biol Bioinform |
2019 |
| 59 |
71.7 |
771 |
Fdataset |
Drug, Disease |
Drug: SMILES, Proten: the amino acid sequence, Diseases: MeSH terms |
RWHNDR (Random Walk on a Heterogeneous Network for Drug Repositioning) |
Random Walk |
Drug Disease Association (DDA) |
NA |
Case studies |
Huntington Disease (HD) |
NA |
NA |
NA |
Top 5 drugs |
29994051 |
IEEE/ACM Trans Comput Biol Bioinform |
2019 |
| 59 |
71.7 |
771 |
Fdataset |
Drug, Disease |
Drug: SMILES, Proten: the amino acid sequence, Diseases: MeSH terms |
RWHNDR (Random Walk on a Heterogeneous Network for Drug Repositioning) |
Random Walk |
Drug Disease Association (DDA) |
NA |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
Top 5 drugs |
29994051 |
IEEE/ACM Trans Comput Biol Bioinform |
2019 |
| 60 |
71.64285714 |
343 |
External _Kinases |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
SDTNBI (Substructure–drug–target network-based inference) |
NetInfer package |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NSAIDs |
NA |
3 targets |
26944082 |
Brief Bioinform |
2017 |
| 60 |
71.64285714 |
343 |
IC |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
SDTNBI (Substructure–drug–target network-based inference) |
NetInfer package |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NSAIDs |
NA |
3 targets |
26944082 |
Brief Bioinform |
2017 |
| 60 |
71.64285714 |
343 |
NR |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
SDTNBI (Substructure–drug–target network-based inference) |
NetInfer package |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NSAIDs |
NA |
3 targets |
26944082 |
Brief Bioinform |
2017 |
| 60 |
71.64285714 |
343 |
Global |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
SDTNBI (Substructure–drug–target network-based inference) |
NetInfer package |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NSAIDs |
NA |
3 targets |
26944082 |
Brief Bioinform |
2017 |
| 60 |
71.64285714 |
343 |
GPCR |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
SDTNBI (Substructure–drug–target network-based inference) |
NetInfer package |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NSAIDs |
NA |
3 targets |
26944082 |
Brief Bioinform |
2017 |
| 60 |
71.64285714 |
343 |
External_GPCR |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
SDTNBI (Substructure–drug–target network-based inference) |
NetInfer package |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NSAIDs |
NA |
3 targets |
26944082 |
Brief Bioinform |
2017 |
| 60 |
71.64285714 |
343 |
Kinases |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
SDTNBI (Substructure–drug–target network-based inference) |
NetInfer package |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NSAIDs |
NA |
3 targets |
26944082 |
Brief Bioinform |
2017 |
| 61 |
71.2 |
997 |
NA |
Drug |
Drug: structure, distance, target |
CATNIP |
XGBoost |
Drug Drug Interaction (DDI) |
https://github.com/coryandar/CATNIP |
Case studies |
Parkinson’s Disease (PD) |
NA |
NA |
NA |
2 drugs |
32764756 |
PLoS Comput Biol |
2020 |
| 61 |
71.2 |
997 |
NA |
Drug |
Drug: structure, distance, target |
CATNIP |
XGBoost |
Drug Drug Interaction (DDI) |
https://github.com/coryandar/CATNIP |
Case studies |
Type 2 Diabetes Mellitus (T2DM) |
NA |
NA |
NA |
1 drug |
32764756 |
PLoS Comput Biol |
2020 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Yohimbine |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Thiopental |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Tacrolimus |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Tolmetin |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Ziprasidone |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Fenoprofen |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Nimodipine |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Citalopram |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Progesterone |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 62 |
71.04 |
361 |
LRSSL |
Drug, Disease |
Drug: chemical fingerprints, target target domain, target gene ontology annotation; Disease: MeSH |
LRSSL (Laplacian regularized sparse subspace learning) |
Laplacian regularized sparse subspace learning |
Drug Disease Association (DDA) |
https://github.com/LiangXujun/LRSSL |
Case studies |
NA |
NA |
Dextromethorphan |
NA |
Top 5 diseases |
28096083 |
Bioinformatics |
2017 |
| 63 |
70.85 |
1798 |
dataset 1 |
Drug, Disease, Gene |
NA |
NEDNBI |
Network-Based Inference |
Drug Disease Association (DDA) |
https://github.com/Qli97/NEDNBI |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 20 drugs |
35338586 |
Mol Inform |
2022 |
| 63 |
70.85 |
1798 |
dataset 2 |
Drug, Disease, Gene |
NA |
NEDNBI |
Network-Based Inference |
Drug Disease Association (DDA) |
https://github.com/Qli97/NEDNBI |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 20 drugs |
35338586 |
Mol Inform |
2022 |
| 64 |
70.8 |
1516 |
Zhang's book |
Side-effect |
Drug: chemical structure, side-effect; Disease: UMLS |
DRDA |
Deep Autoencoder,Adaptive Fusion |
Drug Disease Association (DDA) |
NA |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
34717542 |
BMC Bioinformatics |
2021 |
| 64 |
70.8 |
1516 |
Zhang's book |
Drug, Disease |
Drug: chemical structure, side-effect; Disease: UMLS |
DRDA |
Deep Autoencoder,Adaptive Fusion |
Drug Disease Association (DDA) |
NA |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
34717542 |
BMC Bioinformatics |
2021 |
| 64 |
70.8 |
1516 |
Zhang's book |
Drug, Target |
Drug: chemical structure, side-effect; Disease: UMLS |
DRDA |
Deep Autoencoder,Adaptive Fusion |
Drug Disease Association (DDA) |
NA |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
34717542 |
BMC Bioinformatics |
2021 |
| 65 |
70.4 |
1866 |
Fdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH, Target: sequence |
DDAGDL |
Geometric Deep Learning (GDL),XGBoost |
Drug Disease Association (DDA) |
https://github.com/stevejobws/DDAGDL |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
36125202 |
Brief Bioinform |
2022 |
| 65 |
70.4 |
2046 |
aBiofilm |
Drug |
Drug: SMILES, |
Anti-Biofilm |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
https://bioinfo.imtech.res.in/manojk/antibiofilm/ |
Case studies |
Antimicrobial resistance |
biofilm |
NA |
NA |
Top 25 drugs |
37356913 |
J Mol Biol |
2023 |
| 65 |
70.4 |
1866 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH, Target: sequence |
DDAGDL |
Geometric Deep Learning (GDL),XGBoost |
Drug Disease Association (DDA) |
https://github.com/stevejobws/DDAGDL |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
36125202 |
Brief Bioinform |
2022 |
| 65 |
70.4 |
1866 |
Cdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH, Target: sequence |
DDAGDL |
Geometric Deep Learning (GDL),XGBoost |
Drug Disease Association (DDA) |
https://github.com/stevejobws/DDAGDL |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
36125202 |
Brief Bioinform |
2022 |
| 65 |
70.4 |
1866 |
Cdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH, Target: sequence |
DDAGDL |
Geometric Deep Learning (GDL),XGBoost |
Drug Disease Association (DDA) |
https://github.com/stevejobws/DDAGDL |
Case studies |
Breast cancer |
NA |
NA |
NA |
Top 10 drugs |
36125202 |
Brief Bioinform |
2022 |
| 65 |
70.4 |
1866 |
Fdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH, Target: sequence |
DDAGDL |
Geometric Deep Learning (GDL),XGBoost |
Drug Disease Association (DDA) |
https://github.com/stevejobws/DDAGDL |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
36125202 |
Brief Bioinform |
2022 |
| 65 |
70.4 |
1866 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MeSH, Target: sequence |
DDAGDL |
Geometric Deep Learning (GDL),XGBoost |
Drug Disease Association (DDA) |
https://github.com/stevejobws/DDAGDL |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
36125202 |
Brief Bioinform |
2022 |
| 66 |
70 |
14 |
Fdataset |
Drug, Disease |
Drug: SMILES, Gene sequence , GO, side-effect, PPI network; Diseases: MeSH, Genetic |
PREDICT (PREdicting Drug IndiCaTions) |
Logistic Regression |
Drug Disease Association (DDA) |
NA |
Case studies |
Migrane |
NA |
NA |
NA |
1 drug |
21654673 |
Mol Syst Biol |
2011 |
| 66 |
70 |
14 |
Fdataset |
Drug, Disease |
Drug: SMILES, Gene sequence , GO, side-effect, PPI network; Diseases: MeSH, Genetic |
PREDICT (PREdicting Drug IndiCaTions) |
Logistic Regression |
Drug Disease Association (DDA) |
NA |
Case studies |
Non-papillary renal cell cancer |
NA |
NA |
NA |
1 drug |
21654673 |
Mol Syst Biol |
2011 |
| 67 |
69.8 |
2160 |
DrugRepV |
Drug |
Drug: SMILES, |
Anti-Dengue |
Support Vector Machine (SVM),Artificial Neural Network (ANN),k-Nearest Neighbor (kNN),Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Special studies |
Dengue |
NA |
NA |
NA |
Top 25 drugs |
38257744 |
Viruses |
2023 |
| 68 |
69.4 |
1769 |
NA |
Drug, Target, Pathway |
NA |
MSDF-CNN |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
https://github.com/lemonfino/MSDF-CNN |
Special studies |
Parkinson’s Disease (PD) |
HTR2A |
NA |
NA |
Top 10 drugs |
35897954 |
Molecules |
2022 |
| 69 |
69.38 |
122 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence, Disease: MeSH terms |
TL_HGBI (Triple Layer Heterogeneous Graph Based Inference) |
Heterogeneous Graph Based Inference (HGBI) |
Drug Disease Association (DDA) |
NA |
Case studies |
Alcohol dependence |
NA |
NA |
NA |
Top 10 drugs |
24974205 |
Bioinformatics |
2014 |
| 69 |
69.38 |
122 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence, Disease: MeSH terms |
TL_HGBI (Triple Layer Heterogeneous Graph Based Inference) |
Heterogeneous Graph Based Inference (HGBI) |
Drug Disease Association (DDA) |
NA |
Case studies |
Small Cell Lung Cancer (SCLC) |
NA |
NA |
NA |
Top 10 drugs |
24974205 |
Bioinformatics |
2014 |
| 69 |
69.38 |
122 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence, Disease: MeSH terms |
TL_HGBI (Triple Layer Heterogeneous Graph Based Inference) |
Heterogeneous Graph Based Inference (HGBI) |
Drug Disease Association (DDA) |
NA |
Case studies |
Polysubstance abuse |
NA |
NA |
NA |
Top 10 drugs |
24974205 |
Bioinformatics |
2014 |
| 69 |
69.38 |
122 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence, Disease: MeSH terms |
TL_HGBI (Triple Layer Heterogeneous Graph Based Inference) |
Heterogeneous Graph Based Inference (HGBI) |
Drug Disease Association (DDA) |
NA |
Case studies |
Huntington Disease (HD) |
NA |
NA |
NA |
Top 10 drugs |
24974205 |
Bioinformatics |
2014 |
| 69 |
69.38 |
122 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence, Disease: MeSH terms |
TL_HGBI (Triple Layer Heterogeneous Graph Based Inference) |
Heterogeneous Graph Based Inference (HGBI) |
Drug Disease Association (DDA) |
NA |
Case studies |
Non-Small Cell Lung Cancer (NSCLC) |
NA |
NA |
NA |
Top 10 drugs |
24974205 |
Bioinformatics |
2014 |
| 70 |
69.1 |
1913 |
drug ECR |
Drug, Disease |
NA |
DRONet |
Network embedding (NE) |
Drug Disease Association (DDA) |
https://github.com/yangkuoone/DRONet |
Case studies |
Diabetes |
NA |
NA |
NA |
Top 10 drugs |
36562715 |
Brief Bioinform |
2023 |
| 71 |
68.9 |
2098 |
NA |
Drug, Disease, Target, miRNA |
NA |
MTLDR (Multi-task learning framework for drug repurposing) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
NA |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
37516260 |
Methods |
2023 |
| 71 |
68.9 |
2098 |
NA |
Drug, Disease, Target, miRNA |
NA |
MTLDR (Multi-task learning framework for drug repurposing) |
Graph Convolutional Network (GCN) |
Drug Disease Association (DDA) |
NA |
Case studies |
Tourette's Syndrome |
NA |
NA |
NA |
Top 10 drugs |
37516260 |
Methods |
2023 |
| 72 |
68.8 |
2167 |
GP-KG |
Drug, Disease, Gene |
NA |
MPTN |
CompGCN,Transformer,InteractE |
Drug Disease Association (DDA) |
NA |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
38043469 |
Comput Biol Med |
2024 |
| 72 |
68.8 |
2167 |
OpenBioLink |
Drug, Disease, Target |
NA |
MPTN |
CompGCN,Transformer,InteractE |
Drug Disease Association (DDA) |
NA |
Case studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
38043469 |
Comput Biol Med |
2024 |
| 73 |
68.7 |
2091 |
DGIdb |
Drug, Gene |
NA |
DGCL (Dynamic hyperGraph Contrastive Learning) |
Graph Neural Network (GNN),Multi Layer Perception (MLP) |
Drug Gene Interaction (DGI) |
https://github.com/wentao228/DGCL |
Case studies |
NA |
HMOX1 |
NA |
NA |
Top 10 drugs |
37864294 |
Brief Bioinform |
2023 |
| 73 |
68.7 |
2091 |
LINCS L1000 |
Drug, Gene |
NA |
DGCL (Dynamic hyperGraph Contrastive Learning) |
Graph Neural Network (GNN),Multi Layer Perception (MLP) |
Drug Gene Interaction (DGI) |
https://github.com/wentao228/DGCL |
Case studies |
NA |
HMOX1 |
NA |
NA |
Top 10 drugs |
37864294 |
Brief Bioinform |
2023 |
| 73 |
68.7 |
2091 |
DrugBank |
Drug, Gene |
NA |
DGCL (Dynamic hyperGraph Contrastive Learning) |
Graph Neural Network (GNN),Multi Layer Perception (MLP) |
Drug Gene Interaction (DGI) |
https://github.com/wentao228/DGCL |
Case studies |
NA |
HMOX1 |
NA |
NA |
Top 10 drugs |
37864294 |
Brief Bioinform |
2023 |
| 74 |
68.5 |
672 |
NA |
Gene, Celllines |
NA |
NA |
Deep neural Network (DNN),Support Vector Machine (SVM),Random Forest (RF),Gradient Boosted Machine with trees (GBM),logistic regression with elastic net regularization (EN) |
Drug Disease Association (DDA) |
NA |
Special studies |
Depressive Disorder |
NA |
NA |
NA |
Top 8 drugs |
30010603 |
IEEE J Biomed Health Inform |
2019 |
| 74 |
68.5 |
1768 |
NA |
Drug, Disease, Target |
NA |
NTD-DR |
Nonnegative tensor decomposition |
Drug Disease Association (DDA) |
https://github.com/AliJam82/NTD-DR |
Case studies |
Breast ductal carcinoma, Prostate cancer, Pancreatic neoplasms, Colorectal neoplasms, Small cell lung carcinoma |
NA |
NA |
NA |
Top 50 drugs |
35862409 |
PLoS One |
2022 |
| 74 |
68.5 |
672 |
NA |
Gene, Celllines |
NA |
NA |
Deep neural Network (DNN),Support Vector Machine (SVM),Random Forest (RF),Gradient Boosted Machine with trees (GBM),logistic regression with elastic net regularization (EN) |
Drug Disease Association (DDA) |
NA |
Special studies |
Schizophrenia |
NA |
NA |
NA |
Top 8 drugs |
30010603 |
IEEE J Biomed Health Inform |
2019 |
| 75 |
68.2 |
192 |
NA |
Drug, Disease |
Disease: Phenotypic terms |
PhenoPredict |
The iterative network-based ranking algorithm |
Drug Disease Association (DDA) |
NA |
Special studies |
Schizophrenia |
NA |
NA |
NA |
Top 20 drugs |
26151312 |
J Biomed Inform |
2015 |
| 76 |
67.8 |
2015 |
NA |
Drug, Gene |
NA |
DTSEA (Drug Target Set Enrichment Analysis) |
Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
https://github.com/hanjunwei-lab/DTSEAData |
Special studies |
COVID-19 |
NA |
NA |
NA |
Top 10 drugs |
37105108 |
Comput Biol Med |
2023 |
| 77 |
67 |
1937 |
DNdataset |
Drug, Disease |
Drug: SMILES, Disease: the medical description |
PUON |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
Doxorubicin, Gemcitabine, Vincristine, Methotrexate, Risperidone |
NA |
NA |
Top 5 diseases |
36197871 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 77 |
67 |
1937 |
Ldataset |
Drug, Disease |
Drug: SMILES, Disease: the medical description |
PUON |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
Doxorubicin, Gemcitabine, Vincristine, Methotrexate, Risperidone |
NA |
NA |
Top 5 diseases |
36197871 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 77 |
67 |
1021 |
NA |
Drug, Disease, miRNA |
Drug: chemical structure, side-effect, functional consistency; miRNA: target genes, disease targets; Disease: MeSH |
BIMC |
Bilateral-inductive matrix completion (BIMC) |
Drug Disease Association (DDA) |
https://github.com/Deepthi-K523/BIMC |
Case studies |
NA |
NA |
Almitrine |
NA |
Top 10 diseases |
32583015 |
Mol Genet Genomics |
2020 |
| 77 |
67 |
1937 |
Gottlieb dataset (Fdataset) |
Drug, Disease |
Drug: SMILES, Disease: the medical description |
PUON |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
Doxorubicin, Gemcitabine, Vincristine, Methotrexate, Risperidone |
NA |
NA |
Top 5 diseases |
36197871 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 77 |
67 |
1021 |
NA |
Drug, Disease, miRNA |
Drug: chemical structure, side-effect, functional consistency; miRNA: target genes, disease targets; Disease: MeSH |
BIMC |
Bilateral-inductive matrix completion (BIMC) |
Drug Disease Association (DDA) |
https://github.com/Deepthi-K523/BIMC |
Case studies |
NA |
NA |
Aminolevulinic acid |
NA |
Top 10 diseases |
32583015 |
Mol Genet Genomics |
2020 |
| 77 |
67 |
1937 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: the medical description |
PUON |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
Doxorubicin, Gemcitabine, Vincristine, Methotrexate, Risperidone |
NA |
NA |
Top 5 diseases |
36197871 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 78 |
66.8 |
2181 |
BindingDB |
Drug, Target |
Drug: SMILES |
NA |
Extra tree classifier (ETC) |
Drug Target Interaction (DTI) |
NA |
Special studies |
NA |
Epidermal Growth Factor Receptor (EGFR) |
NA |
NA |
Top 9 drugs |
38000720 |
Eur J Pharmacol |
2024 |
| 79 |
66.65 |
1973 |
RepoDB |
Drug, Disease |
NA |
DrugRep-KG |
Logistic Regression |
Drug Disease Association (DDA) |
https://github.com/CBRC-lab/DrugRep-KG |
Case studies |
Contact Dermatitis |
NA |
NA |
NA |
Top 2 drugs |
37023229 |
J Chem Inf Model |
2023 |
| 79 |
66.65 |
1973 |
Negative set |
Drug, Disease |
NA |
DrugRep-KG |
Logistic Regression |
Drug Disease Association (DDA) |
https://github.com/CBRC-lab/DrugRep-KG |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 6 drugs |
37023229 |
J Chem Inf Model |
2023 |
| 79 |
66.65 |
1973 |
RepoDB |
Drug, Disease |
NA |
DrugRep-KG |
Logistic Regression |
Drug Disease Association (DDA) |
https://github.com/CBRC-lab/DrugRep-KG |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 6 drugs |
37023229 |
J Chem Inf Model |
2023 |
| 79 |
66.65 |
1973 |
Negative set |
Drug, Disease |
NA |
DrugRep-KG |
Logistic Regression |
Drug Disease Association (DDA) |
https://github.com/CBRC-lab/DrugRep-KG |
Case studies |
Atopic Eczema |
NA |
NA |
NA |
Top 4 drugs |
37023229 |
J Chem Inf Model |
2023 |
| 79 |
66.65 |
1973 |
Negative set |
Drug, Disease |
NA |
DrugRep-KG |
Logistic Regression |
Drug Disease Association (DDA) |
https://github.com/CBRC-lab/DrugRep-KG |
Case studies |
Contact Dermatitis |
NA |
NA |
NA |
Top 2 drugs |
37023229 |
J Chem Inf Model |
2023 |
| 79 |
66.65 |
1973 |
RepoDB |
Drug, Disease |
NA |
DrugRep-KG |
Logistic Regression |
Drug Disease Association (DDA) |
https://github.com/CBRC-lab/DrugRep-KG |
Case studies |
Atopic Eczema |
NA |
NA |
NA |
Top 4 drugs |
37023229 |
J Chem Inf Model |
2023 |
| 80 |
66.4 |
1990 |
LRSSL |
Drug, Disease |
NA |
NetPro |
Label Propagation |
Drug Disease Association (DDA) |
https://github.com/hyr0771/NetPro |
Case studies |
NA |
NA |
Levodopa, Flecainide, Doxorubicin |
NA |
Top 5 diseases |
37018341 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 80 |
66.4 |
1990 |
PREDICT (Fdataset) |
Drug, Disease |
NA |
NetPro |
Label Propagation |
Drug Disease Association (DDA) |
https://github.com/hyr0771/NetPro |
Case studies |
NA |
NA |
Levodopa, Flecainide, Doxorubicin |
NA |
Top 5 diseases |
37018341 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 80 |
66.4 |
1990 |
Cdataset |
Drug, Disease |
NA |
NetPro |
Label Propagation |
Drug Disease Association (DDA) |
https://github.com/hyr0771/NetPro |
Case studies |
NA |
NA |
Levodopa, Flecainide, Doxorubicin |
NA |
Top 5 diseases |
37018341 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 81 |
66.2 |
386 |
Yamanishi_GPCR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
DNA topoisomerase 2-alpha (P11388) |
NA |
NA |
31 drugs |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_IC |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Astemizole |
NA |
14 targets |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_NR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_GPCR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_IC |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
DNA topoisomerase 2-alpha (P11388) |
NA |
NA |
31 drugs |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_E |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Astemizole |
NA |
14 targets |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_NR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Astemizole |
NA |
14 targets |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_IC |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_E |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
DNA topoisomerase 2-alpha (P11388) |
NA |
NA |
31 drugs |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_E |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_NR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
DNA topoisomerase 2-alpha (P11388) |
NA |
NA |
31 drugs |
28808275 |
Sci Rep |
2017 |
| 81 |
66.2 |
386 |
Yamanishi_GPCR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
Astemizole |
NA |
14 targets |
28808275 |
Sci Rep |
2017 |
| 82 |
65.5 |
2087 |
NA |
Drug, Disease, Target, Side-effect |
Drug: SMILES, Target: the amino acid sequences |
BG-DTI |
Convolutional Neural Network (CNN),Graph Neural Network (GNN),Graph Attention Network (GAT),Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
https://github.com/wyx2012/BG-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
37764321 |
Molecules |
2023 |
| 83 |
64.9 |
1306 |
NA |
Drug, Virus |
Drug: chemical structure, Virus: d2* dissimilarity/distance (at k=6) between the viral genome sequences |
DVA (Drug Virus Association) |
Matrix Completion |
Drug Virus Association (DVA) |
www.github.com/AanchalMongia/DVA |
Case studies |
COVID-19 |
SARS-CoV-2 |
NA |
NA |
Top 6 drugs |
33907209 |
Sci Rep |
2021 |
| 84 |
64.8 |
1814 |
NA |
Drug, chemical |
NA |
NA |
Knowledge Graph Embedding |
Drug Disease Association (DDA) |
NA |
Special studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
36180861 |
BMC Bioinformatics |
2022 |
| 85 |
64.6 |
2116 |
NA |
Drug |
Drug: SMILES |
NA |
Graph Convolutional Network (GCN),XGBoost |
Drug Target Interaction (DTI) |
NA |
Special studies |
Parkinson’s Disease (PD) |
PINK1 (Phosphatase and Tensin homologue-induced kinase 1) |
NA |
NA |
Top 22 drugs |
37544165 |
Comput Methods Programs Biomed |
2023 |
| 86 |
64.5 |
968 |
Dataset 1 |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence Disease: MeSH |
iDrug |
Matrix Completion |
Drug Target Interaction (DTI) |
https://github.com/Case-esaC/iDrug |
NA |
NA |
NA |
NA |
NA |
NA |
32667925 |
PLoS Comput Biol |
2020 |
| 86 |
64.5 |
968 |
Fdataset (Dataset 2) |
Drug, Disease, Target |
Drug: SMILES, Target: target sequence Disease: MeSH |
iDrug |
Matrix Completion |
Drug Target Interaction (DTI) |
https://github.com/Case-esaC/iDrug |
NA |
NA |
NA |
NA |
NA |
NA |
32667925 |
PLoS Comput Biol |
2020 |
| 87 |
63.7 |
1856 |
NA |
Drug, Disease, Target, Side-effect |
NA |
DTI-GTN |
Graph Transformer Network |
Drug Target Interaction (DTI) |
https://github.com/q498756498/DTI-GTN |
Case studies |
NA |
HTR1A |
NA |
NA |
Top 4 drugs |
36329406 |
BMC Bioinformatics |
2022 |
| 87 |
63.7 |
1856 |
NA |
Drug, Disease, Target, Side-effect |
NA |
DTI-GTN |
Graph Transformer Network |
Drug Target Interaction (DTI) |
https://github.com/q498756498/DTI-GTN |
Case studies |
NA |
CHRM3 |
NA |
NA |
Top 2 drugs |
36329406 |
BMC Bioinformatics |
2022 |
| 88 |
63.2 |
356 |
Yamanishi_NR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 88 |
63.2 |
356 |
NA |
Drug, Disease, Target |
NA |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 88 |
63.2 |
356 |
Yamanishi_E |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 88 |
63.2 |
356 |
Yamanishi_IC |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 88 |
63.2 |
356 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 89 |
62.9 |
36 |
NA |
Drug, Disease, Target, Gene, Pathway |
NA |
CauseNet |
Computing transition weights |
Drug Disease Association (DDA) |
NA |
Case studies |
Crohn's disease (CD) |
NA |
NA |
NA |
Top 5 drugs |
24564553 |
BMC Bioinformatics |
2013 |
| 90 |
62.5 |
736 |
Cdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
ANMF |
Additional Neural Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/MortySn/ANMF |
NA |
NA |
NA |
NA |
NA |
NA |
31412762 |
BMC Bioinformatics |
2019 |
| 90 |
62.5 |
736 |
Fdataset |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
ANMF |
Additional Neural Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/MortySn/ANMF |
NA |
NA |
NA |
NA |
NA |
NA |
31412762 |
BMC Bioinformatics |
2019 |
| 91 |
61.8 |
1096 |
NA |
Drug, Target |
Drug: SMILES, Target: sequence |
DLDTI |
Representation learning,Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/CUMTzackGit/DLDTI |
Case studies |
Atherosclerosis |
NA |
Tetramethylpyrazine |
NA |
288 targets |
33187537 |
J Transl Med |
2020 |
| 92 |
60.9 |
1340 |
IC |
Drug, Target |
Drug: SMILES, Target: Sequence |
DTI-MLCD |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/a96123155/DTI-MLCD |
NA |
NA |
NA |
NA |
NA |
NA |
32964234 |
Brief Bioinform |
2021 |
| 92 |
60.9 |
1340 |
GPCR |
Drug, Target |
Drug: SMILES, Target: Sequence |
DTI-MLCD |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/a96123155/DTI-MLCD |
NA |
NA |
NA |
NA |
NA |
NA |
32964234 |
Brief Bioinform |
2021 |
| 92 |
60.9 |
1340 |
NR |
Drug, Target |
Drug: SMILES, Target: Sequence |
DTI-MLCD |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/a96123155/DTI-MLCD |
NA |
NA |
NA |
NA |
NA |
NA |
32964234 |
Brief Bioinform |
2021 |
| 92 |
60.9 |
1340 |
E |
Drug, Target |
Drug: SMILES, Target: Sequence |
DTI-MLCD |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/a96123155/DTI-MLCD |
NA |
NA |
NA |
NA |
NA |
NA |
32964234 |
Brief Bioinform |
2021 |
| 93 |
60.6 |
2208 |
NELL-One |
NA |
NA |
MLAN (Multi-Level Attention Network) |
Gated Mechanism,Attention Mechanism,MTransD,Commonality Relation Learner (CRL) |
Drug Disease Association (DDA) |
NA |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 5 drugs |
38244473 |
Comput Biol Med |
2024 |
| 93 |
60.6 |
2208 |
BIOKG-One |
Drug, Disease, Target, Side-effect, |
NA |
MLAN (Multi-Level Attention Network) |
Gated Mechanism,Attention Mechanism,MTransD,Commonality Relation Learner (CRL) |
Drug Disease Association (DDA) |
NA |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 5 drugs |
38244473 |
Comput Biol Med |
2024 |
| 93 |
60.6 |
2208 |
COVID19-One |
NA |
NA |
MLAN (Multi-Level Attention Network) |
Gated Mechanism,Attention Mechanism,MTransD,Commonality Relation Learner (CRL) |
Drug Disease Association (DDA) |
NA |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 5 drugs |
38244473 |
Comput Biol Med |
2024 |
| 94 |
60.5 |
1980 |
Ovarian Cancer Dataset |
Drug, Gene |
NA |
SPLNMTF (Self-Paced Non-negative Matrix Tri-Factorization) |
Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/qi0906/SPLNMTF |
NA |
NA |
NA |
NA |
NA |
NA |
36445996 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 94 |
60.5 |
1980 |
Acute myeloid leukemia (AML) dataset |
Drug, Gene |
NA |
SPLNMTF (Self-Paced Non-negative Matrix Tri-Factorization) |
Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/qi0906/SPLNMTF |
NA |
NA |
NA |
NA |
NA |
NA |
36445996 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 95 |
60.1 |
1867 |
Yamanishi |
NA |
NA |
MHADTI (Multiview heterogeneous information network embedding with Hierarchical Attention mechanisms to discover potential Drug–Target Interaction) |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/pxystudy/MHADTI |
Case studies |
NA |
NA |
Pregabalin,Oxycodone,Sunitinib,Acetaminophen,Gefitinib |
NA |
NA |
36242566 |
Brief Bioinform |
2022 |
| 95 |
60.1 |
1867 |
NEDTP |
NA |
NA |
MHADTI (Multiview heterogeneous information network embedding with Hierarchical Attention mechanisms to discover potential Drug–Target Interaction) |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/pxystudy/MHADTI |
Case studies |
NA |
NA |
Pregabalin,Oxycodone,Sunitinib,Acetaminophen,Gefitinib |
NA |
NA |
36242566 |
Brief Bioinform |
2022 |
| 95 |
60.1 |
1867 |
NA |
Drug, Target |
Drug: SMILES, Disease: MeSH, Target: sequence |
MHADTI (Multiview heterogeneous information network embedding with Hierarchical Attention mechanisms to discover potential Drug–Target Interaction) |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/pxystudy/MHADTI |
Case studies |
NA |
NA |
Pregabalin,Oxycodone,Sunitinib,Acetaminophen,Gefitinib |
NA |
NA |
36242566 |
Brief Bioinform |
2022 |
| 95 |
60.1 |
1867 |
DTINet |
NA |
NA |
MHADTI (Multiview heterogeneous information network embedding with Hierarchical Attention mechanisms to discover potential Drug–Target Interaction) |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/pxystudy/MHADTI |
Case studies |
NA |
NA |
Pregabalin,Oxycodone,Sunitinib,Acetaminophen,Gefitinib |
NA |
NA |
36242566 |
Brief Bioinform |
2022 |
| 95 |
60.1 |
1867 |
AGHEL |
NA |
NA |
MHADTI (Multiview heterogeneous information network embedding with Hierarchical Attention mechanisms to discover potential Drug–Target Interaction) |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/pxystudy/MHADTI |
Case studies |
NA |
NA |
Pregabalin,Oxycodone,Sunitinib,Acetaminophen,Gefitinib |
NA |
NA |
36242566 |
Brief Bioinform |
2022 |
| 96 |
60.0875 |
2176 |
Yamanishi_GPCR |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 96 |
60.0875 |
2176 |
BIOSNAP |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 96 |
60.0875 |
2176 |
Yamanishi_IC |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 96 |
60.0875 |
2176 |
BindingDB |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 96 |
60.0875 |
2176 |
Davis |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 96 |
60.0875 |
2176 |
Yamanishi_NR |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 96 |
60.0875 |
2176 |
Yamanishi_E |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 96 |
60.0875 |
2176 |
DrugBank (version 5.1.9) |
Drug, Target |
Target: 20D Vector, Drug: SMILES |
geNnius (Graph Embedding Neural Network Interaction Uncovering System) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/ubioinformat/GeNNius |
NA |
NA |
NA |
NA |
NA |
NA |
38134424 |
Bioinformatics |
2024 |
| 97 |
60 |
2001 |
Davis |
Drug, Target |
NA |
BindingSite-AugmentedDTA |
Graph Neural Network (GNN) |
Drug Target binding Affinity (DTA) |
https://github.com/yazdanimehdi/BindingSite-AugmentedDTA |
Case studies |
COVID-19 |
SARS-CoV-2 (3C-like protease, RNA-dependent RNA polymerase(RdRp), helicase, Spike/ACE2 complex) |
NA |
NA |
Top 10 drugs |
37096593 |
Brief Bioinform |
2023 |
| 97 |
60 |
2001 |
KIBA |
Drug, Target |
NA |
BindingSite-AugmentedDTA |
Graph Neural Network (GNN) |
Drug Target binding Affinity (DTA) |
https://github.com/yazdanimehdi/BindingSite-AugmentedDTA |
Case studies |
COVID-19 |
SARS-CoV-2 (3C-like protease, RNA-dependent RNA polymerase(RdRp), helicase, Spike/ACE2 complex) |
NA |
NA |
Top 10 drugs |
37096593 |
Brief Bioinform |
2023 |
| 98 |
59.9 |
1060 |
NA |
Drug, Disease, Target, Gene |
NA |
RepCOOL |
Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
Case studies |
Breast cancer stage II |
NA |
NA |
NA |
Top 4 drugs |
33008415 |
J Transl Med |
2020 |
| 99 |
59.7 |
1140 |
NA |
Chemical molecules, Gene, Gene expression profiles |
NA |
MNBDR (Module Network Based Drug Repositioning)LINC1000,Cmap |
Random Walk |
Drug Disease Association (DDA) |
https://github.com/nbnbhwyy/MNBDR |
Case studies |
Breast cancer |
NA |
NA |
NA |
NA |
33375395 |
Genes (Basel) |
2020 |
| 99 |
59.7 |
1140 |
Golden standard |
Drug, Disease |
NA |
MNBDR (Module Network Based Drug Repositioning)LINC1000,Cmap |
Random Walk |
Drug Disease Association (DDA) |
https://github.com/nbnbhwyy/MNBDR |
Case studies |
Breast cancer |
NA |
NA |
NA |
NA |
33375395 |
Genes (Basel) |
2020 |
| 100 |
59.6 |
415 |
Kinase (K) dataset |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
BRDTI |
Bayesian |
Drug Target Interaction (DTI) |
https://github.com/lpeska/BRDTI |
NA |
NA |
NA |
NA |
NA |
NA |
29054256 |
Comput Methods Programs Biomed |
2017 |
| 100 |
59.6 |
415 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
BRDTI |
Bayesian |
Drug Target Interaction (DTI) |
https://github.com/lpeska/BRDTI |
NA |
NA |
NA |
NA |
NA |
NA |
29054256 |
Comput Methods Programs Biomed |
2017 |
| 100 |
59.6 |
415 |
Yamanishi_E |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
BRDTI |
Bayesian |
Drug Target Interaction (DTI) |
https://github.com/lpeska/BRDTI |
NA |
NA |
NA |
NA |
NA |
NA |
29054256 |
Comput Methods Programs Biomed |
2017 |
| 100 |
59.6 |
415 |
Yamanishi_NR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
BRDTI |
Bayesian |
Drug Target Interaction (DTI) |
https://github.com/lpeska/BRDTI |
NA |
NA |
NA |
NA |
NA |
NA |
29054256 |
Comput Methods Programs Biomed |
2017 |
| 100 |
59.6 |
415 |
Yamanishi_IC |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
BRDTI |
Bayesian |
Drug Target Interaction (DTI) |
https://github.com/lpeska/BRDTI |
NA |
NA |
NA |
NA |
NA |
NA |
29054256 |
Comput Methods Programs Biomed |
2017 |
| 101 |
59.2 |
140 |
Fdataset |
Drug, Disease |
NA |
NA |
ProbS and HeatS |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Felodipine |
NA |
Top 10 diseases |
25969690 |
Comput Math Methods Med |
2015 |
| 101 |
59.2 |
140 |
Fdataset |
Drug, Disease |
NA |
NA |
ProbS and HeatS |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Aspirin |
NA |
Top 10 diseases |
25969690 |
Comput Math Methods Med |
2015 |
| 101 |
59.2 |
140 |
Fdataset |
Drug, Disease |
NA |
NA |
ProbS and HeatS |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
Tamoxifen |
NA |
Top 10 diseases |
25969690 |
Comput Math Methods Med |
2015 |
| 102 |
58.9 |
1260 |
NA |
Subject, object, predicate |
NA |
LBD |
Knowledge Graph Completion |
Drug Disease Association (DDA) |
https://github.com/kilicogluh/lbd-covid |
Special studies |
COVID-19 |
NA |
NA |
NA |
5 drugs |
33571675 |
J Biomed Inform |
2021 |
| 103 |
58.7 |
725 |
NA |
Drug, Disease, Target |
Drug: drug-target target |
NA |
CLASH (Complementary Linkage with Anchoring and Scoring),Graph-based Semi-Supervised Learning (SSL) |
Drug Drug Interaction (DDI) |
NA |
Case studies |
Vascular dementia |
NA |
NA |
NA |
Top 11 drug |
31337333 |
BMC Bioinformatics |
2019 |
| 104 |
58.5 |
1132 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: medical description data |
HAMN (Hybrid Attentional Memory Network) |
Collaborative Filtering,Autoencoder |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33297947 |
BMC Bioinformatics |
2020 |
| 104 |
58.5 |
1132 |
Cdataset |
Drug, Disease |
Drug: SMILES, Disease: medical description data |
HAMN (Hybrid Attentional Memory Network) |
Collaborative Filtering,Autoencoder |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33297947 |
BMC Bioinformatics |
2020 |
| 104 |
58.5 |
1322 |
NA |
Drug, Gene |
NA |
NA |
Deep Autoencoder,XGBoost |
Drug Target Interaction (DTI) |
https://github.com/tsjshg/ai-drug-dev |
Special studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 20 drugs |
33941241 |
Alzheimers Res Ther |
2021 |
| 105 |
57 |
1719 |
Own dataset |
Drug, Target |
Drug: side-effects, drug chemical structure, drug physicochemical properties and therapeutic properties, Target: co-pathway, PPI network, Gene Ontology and gene-encoded target sequence |
DTI-HETA |
Graph Neural Network (GNN),Graph Attention Network (GAT) |
Drug Target Interaction (DTI) |
https://github.com/ZhangyuXM/DTI-HETA |
NA |
NA |
NA |
NA |
NA |
NA |
35380622 |
Brief Bioinform |
2022 |
| 105 |
57 |
2144 |
KIBA |
Drug, Target |
Drug: SMILES, Target: The amino acid Sequence. |
TeM-DTBA (Time-efficient Multimodal Drug Target Binding Affinity) |
Multi Layer Perception (MLP) |
Drug Target binding Affinity (DTA) |
https://github.com/hkmztrk/DeepDTA/tree/master/data. |
NA |
NA |
NA |
NA |
NA |
NA |
37777631 |
J Comput Aided Mol Des |
2023 |
| 105 |
57 |
1719 |
Yamanishi_E |
Drug, Target |
Drug: side-effects, drug chemical structure, drug physicochemical properties and therapeutic properties, Target: co-pathway, PPI network, Gene Ontology and gene-encoded target sequence |
DTI-HETA |
Graph Neural Network (GNN),Graph Attention Network (GAT) |
Drug Target Interaction (DTI) |
https://github.com/ZhangyuXM/DTI-HETA |
NA |
NA |
NA |
NA |
NA |
NA |
35380622 |
Brief Bioinform |
2022 |
| 105 |
57 |
1719 |
Yamanishi_IC |
Drug, Target |
Drug: side-effects, drug chemical structure, drug physicochemical properties and therapeutic properties, Target: co-pathway, PPI network, Gene Ontology and gene-encoded target sequence |
DTI-HETA |
Graph Neural Network (GNN),Graph Attention Network (GAT) |
Drug Target Interaction (DTI) |
https://github.com/ZhangyuXM/DTI-HETA |
NA |
NA |
NA |
NA |
NA |
NA |
35380622 |
Brief Bioinform |
2022 |
| 105 |
57 |
2144 |
Davis |
Drug, Target |
Drug: SMILES, Target: The amino acid Sequence. |
TeM-DTBA (Time-efficient Multimodal Drug Target Binding Affinity) |
Multi Layer Perception (MLP) |
Drug Target binding Affinity (DTA) |
https://github.com/hkmztrk/DeepDTA/tree/master/data. |
NA |
NA |
NA |
NA |
NA |
NA |
37777631 |
J Comput Aided Mol Des |
2023 |
| 106 |
56.76 |
1695 |
Yamanishi_NR |
Drug, Target |
Drug: chemical substructures, Target: the primary sequences |
DT2Vec |
XGBoost |
Drug Target Interaction (DTI) |
https://github.com/elmira-amiri/DT2Vec |
NA |
NA |
NA |
NA |
NA |
NA |
35379165 |
BMC Bioinformatics |
2022 |
| 106 |
56.76 |
1695 |
CheMBL |
Drug, Target |
Drug: chemical substructures, Target: the primary sequences |
DT2Vec |
XGBoost |
Drug Target Interaction (DTI) |
https://github.com/elmira-amiri/DT2Vec |
NA |
NA |
NA |
NA |
NA |
NA |
35379165 |
BMC Bioinformatics |
2022 |
| 106 |
56.76 |
1695 |
Yamanishi_E |
Drug, Target |
Drug: chemical substructures, Target: the primary sequences |
DT2Vec |
XGBoost |
Drug Target Interaction (DTI) |
https://github.com/elmira-amiri/DT2Vec |
NA |
NA |
NA |
NA |
NA |
NA |
35379165 |
BMC Bioinformatics |
2022 |
| 106 |
56.76 |
1695 |
Yamanishi_IC |
Drug, Target |
Drug: chemical substructures, Target: the primary sequences |
DT2Vec |
XGBoost |
Drug Target Interaction (DTI) |
https://github.com/elmira-amiri/DT2Vec |
NA |
NA |
NA |
NA |
NA |
NA |
35379165 |
BMC Bioinformatics |
2022 |
| 106 |
56.76 |
1695 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical substructures, Target: the primary sequences |
DT2Vec |
XGBoost |
Drug Target Interaction (DTI) |
https://github.com/elmira-amiri/DT2Vec |
NA |
NA |
NA |
NA |
NA |
NA |
35379165 |
BMC Bioinformatics |
2022 |
| 107 |
56.6 |
380 |
NA |
Drug, Gene |
Drug: UniProt ID, |
PD-MRW |
Random Walk |
Drug Gene Association (DGA) |
NA |
Case studies |
Hepatocellular Carcinoma |
NA |
NA |
NA |
Top 20 drugs |
27076463 |
IEEE/ACM Trans Comput Biol Bioinform |
2017 |
| 108 |
56.5 |
1546 |
NA |
Drug, Disease, Gene |
NA |
GCAN (GRU-Cooperation-Attention-Network) |
GRU-Cooperation-Attention-Network (GCAN),RNN,Biased random walk |
Drug Disease Association (DDA) |
NA |
Case studies |
type I Gaucher disease |
NA |
NA |
NA |
Top 2 drugs |
34789254 |
BMC Med Inform Decis Mak |
2021 |
| 109 |
55.5 |
816 |
NA |
Drug, Target |
Drug: chemical structure, Target: GO terms |
OCSVM (One-class Support Vector Machine) |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
Additional file 4 |
NA |
NA |
NA |
NA |
NA |
NA |
31881829 |
BMC Bioinformatics |
2019 |
| 110 |
55.4 |
1915 |
NA |
Drug, Gene |
NA |
NA |
Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
NA |
Special studies |
Non-Small Cell Lung Cancer (NSCLC) |
NA |
NA |
NA |
Top 11 drugs |
36768566 |
Int J Mol Sci |
2023 |
| 110 |
55.4 |
1915 |
NA |
Drug, Gene |
NA |
NA |
Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
NA |
Special studies |
Colorectal Cancer |
NA |
NA |
NA |
Top 9 drugs |
36768566 |
Int J Mol Sci |
2023 |
| 111 |
55 |
1674 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
Affinity2Vec |
XGBoost |
Drug Target binding Affinity (DTA) |
https://github.com/MahaThafar/Affinity2Vec |
NA |
NA |
NA |
NA |
NA |
NA |
35306525 |
Sci Rep |
2022 |
| 111 |
55 |
1674 |
KIBA |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
Affinity2Vec |
XGBoost |
Drug Target binding Affinity (DTA) |
https://github.com/MahaThafar/Affinity2Vec |
NA |
NA |
NA |
NA |
NA |
NA |
35306525 |
Sci Rep |
2022 |
| 112 |
54.5 |
1567 |
NeoDTI |
Drug, Disease, Target, Side-effect |
Drug: SMILES, Target: target sequence |
MultiDTI (Multi-modal DTI) |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/Deshan-Zhou/MultiDTI/ |
NA |
NA |
NA |
NA |
NA |
NA |
34180970 |
Bioinformatics |
2021 |
| 113 |
53.5 |
475 |
Dataset 1 |
Drug, Disease |
Drug: drug substructures, target target functional domain and GO annotations, Diseases: MeSH terms |
DR2DI |
Regularized Kernel Classifier |
Drug Disease Association (DDA) |
https://github.com/huayu1111/DR2DI |
NA |
NA |
NA |
NA |
NA |
NA |
29687309 |
J Comput Aided Mol Des |
2018 |
| 113 |
53.5 |
2169 |
DRKG |
Drug, Disease, Gene, Pathway, Side-effect, Compound, Anatomy, Tax, Molecular Function, Symptom, Biological Process, Cellular Component, Atc, PharmacologicClass |
NA |
TransRGNN |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
NA |
Case studies |
COVID-19 |
NA |
NA |
NA |
Top 30 drugs |
38104883 |
Methods |
2024 |
| 113 |
53.5 |
586 |
NA |
Drug, Disease |
Drug: PubChem fingerprints, Disease: MeSH |
DrPOCS (projection onto convex sets) |
Matrix Completion |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
29993698 |
IEEE/ACM Trans Comput Biol Bioinform |
2019 |
| 114 |
53 |
1748 |
C.elegans |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MHSADTI |
Graph Attention Network (GAT),Multi-head self-attention mechanism |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33956632 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 114 |
53 |
1748 |
DUD-E |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MHSADTI |
Graph Attention Network (GAT),Multi-head self-attention mechanism |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33956632 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 114 |
53 |
856 |
LRSSL |
Drug, Disease |
Drug: chemical structure, drug target domain, drug target gene ontology (GO); Disease: semantic |
DDAPRED |
Logistic Matrix Factorization |
Drug Disease Association (DDA) |
https://github.com/nongdaxiaofeng/DDAPRED |
NA |
NA |
NA |
NA |
NA |
NA |
32062701 |
J Mol Model |
2020 |
| 114 |
53 |
1748 |
DrugBank |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MHSADTI |
Graph Attention Network (GAT),Multi-head self-attention mechanism |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33956632 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 114 |
53 |
1748 |
Human |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MHSADTI |
Graph Attention Network (GAT),Multi-head self-attention mechanism |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33956632 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 115 |
52.98571429 |
973 |
dataset1_PK |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset1_GPCR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset1_TR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset1_NR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
Yamanishi_NR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
Yamanishi_E |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset2_David |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset1_CR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset1_E |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset1_IC |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
Yamanishi_IC |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset2_Ketz |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 115 |
52.98571429 |
973 |
dataset1_CSM |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
DTIP_MDHN |
Index kernel matrix |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32703151 |
BMC Bioinformatics |
2020 |
| 116 |
52.75 |
1659 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GEFA (Graph Early Fusion Affinity) |
Graph Convolutional Network (GCN) |
Drug Target binding Affinity (DTA) |
https://github.com/ngminhtri0394/GEFA |
NA |
NA |
NA |
NA |
NA |
NA |
34197324 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 116 |
52.75 |
1659 |
PDBBind |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
GEFA (Graph Early Fusion Affinity) |
Graph Convolutional Network (GCN) |
Drug Target binding Affinity (DTA) |
https://github.com/ngminhtri0394/GEFA |
NA |
NA |
NA |
NA |
NA |
NA |
34197324 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 117 |
52.4 |
1717 |
D1 |
Drug, Target |
NA |
MccDTI |
Deep Autoencoder,Matrix Completion |
Drug Target Interaction (DTI) |
https://github.com/ShangCS/MccDTI |
NA |
NA |
NA |
NA |
NA |
NA |
35262678 |
Brief Bioinform |
2022 |
| 117 |
52.4 |
1717 |
D2 |
Drug, Target |
NA |
MccDTI |
Deep Autoencoder,Matrix Completion |
Drug Target Interaction (DTI) |
https://github.com/ShangCS/MccDTI |
NA |
NA |
NA |
NA |
NA |
NA |
35262678 |
Brief Bioinform |
2022 |
| 118 |
51.85 |
1518 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DTI-End-to-End-DL |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/larngroup/DTI-End-to-End-DL |
NA |
NA |
NA |
NA |
NA |
NA |
32142454 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 118 |
51.85 |
1518 |
DrugBank |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DTI-End-to-End-DL |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/larngroup/DTI-End-to-End-DL |
NA |
NA |
NA |
NA |
NA |
NA |
32142454 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 118 |
51.85 |
1518 |
Yamanishi |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DTI-End-to-End-DL |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/larngroup/DTI-End-to-End-DL |
NA |
NA |
NA |
NA |
NA |
NA |
32142454 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 118 |
51.85 |
1518 |
BioLip |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DTI-End-to-End-DL |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/larngroup/DTI-End-to-End-DL |
NA |
NA |
NA |
NA |
NA |
NA |
32142454 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 119 |
51.5 |
1838 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DeepLPI |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Target Interaction (DTI) |
https://github.com/David-BominWei/DeepLPI |
NA |
NA |
NA |
NA |
NA |
NA |
36307509 |
Sci Rep |
2022 |
| 119 |
51.5 |
1838 |
COVID19-One |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DeepLPI |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Target Interaction (DTI) |
https://github.com/David-BominWei/DeepLPI |
NA |
NA |
NA |
NA |
NA |
NA |
36307509 |
Sci Rep |
2022 |
| 119 |
51.5 |
1838 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DeepLPI |
Convolutional Neural Network (CNN),Bidirectional Long Short-Term Memory (Bi-LSTM) |
Drug Target Interaction (DTI) |
https://github.com/David-BominWei/DeepLPI |
NA |
NA |
NA |
NA |
NA |
NA |
36307509 |
Sci Rep |
2022 |
| 120 |
51.4 |
1056 |
NA |
Drug, Target |
Drug: chemical structure |
PIMD |
Similarity Network Fusion (SNF) |
Drug Drug Interaction (DDI) |
https://github.com/Sepstar/PIMD/ |
Case studies |
NA |
NA |
NA |
NA |
NA |
33075523 |
Genomics Proteomics Bioinformatics |
2020 |
| 121 |
51 |
1678 |
Davis |
Drug, Target |
Drug: 2D chemical structure, Target: sequence |
NerLTR-DTA |
Learning To Rank (LTR) |
Drug Target binding Affinity (DTA) |
https://github.com/RUXIAOQING964914140/NerLTR-DTA |
NA |
NA |
NA |
NA |
NA |
NA |
35134828 |
Bioinformatics |
2022 |
| 121 |
51 |
1678 |
KIBA |
Drug, Target |
Drug: 2D chemical structure, Target: sequence |
NerLTR-DTA |
Learning To Rank (LTR) |
Drug Target binding Affinity (DTA) |
https://github.com/RUXIAOQING964914140/NerLTR-DTA |
NA |
NA |
NA |
NA |
NA |
NA |
35134828 |
Bioinformatics |
2022 |
| 122 |
50.75 |
2018 |
Yamanishi |
Drug, Target |
NA |
DEDTI-IEDTI |
Deep Neural Network (DNN) |
Drug Target Interaction (DTI) |
https://github.com/BioinformaticsIASBS/IEDTI-DEDTI |
Case studies |
NA |
NA |
NA |
NA |
Top 126 drugs |
37286613 |
Sci Rep |
2023 |
| 122 |
50.75 |
2018 |
DTINet |
Drug, Target |
NA |
DEDTI-IEDTI |
Deep Neural Network (DNN) |
Drug Target Interaction (DTI) |
https://github.com/BioinformaticsIASBS/IEDTI-DEDTI |
Case studies |
NA |
NA |
NA |
NA |
Top 126 drugs |
37286613 |
Sci Rep |
2023 |
| 123 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Dysmenorrhea |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 123 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Psoriasis |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 123 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Urticaria |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 123 |
50.5 |
794 |
NA |
Drug, Target |
Drug: SMILES, Proten: the amino acid sequence |
BANDIT |
Bayesian |
Drug Target Interaction (DTI) |
Select pieces of custom code can be made available upon request. |
NA |
NA |
NA |
NA |
NA |
NA |
31745082 |
Nat Commun |
2019 |
| 123 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 123 |
50.5 |
2000 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: the amino acid sequences |
DT2Vec+ |
XGBoost |
Drug Target Interaction (DTI) |
https://github.com/elmira-amiri/DT2VecPlus |
NA |
NA |
NA |
NA |
NA |
NA |
37193964 |
BMC Bioinformatics |
2023 |
| 123 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Chronic lymphocytic leukemia |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 124 |
50.3 |
1787 |
Yamanishi_NR |
Drug, Target |
Drug: chemical structure, target: protein sequence |
Ro-DNILMF |
Integrated logistic matrix factorization |
Drug Target Interaction (DTI) |
https://github.com/LJX0326/Ro-DNILMF.git |
NA |
NA |
NA |
NA |
NA |
NA |
36014371 |
Molecules |
2022 |
| 124 |
50.3 |
1787 |
Yamanishi_E |
Drug, Target |
Drug: chemical structure, target: protein sequence |
Ro-DNILMF |
Integrated logistic matrix factorization |
Drug Target Interaction (DTI) |
https://github.com/LJX0326/Ro-DNILMF.git |
NA |
NA |
NA |
NA |
NA |
NA |
36014371 |
Molecules |
2022 |
| 124 |
50.3 |
1787 |
Yamanishi_IC |
Drug, Target |
Drug: chemical structure, target: protein sequence |
Ro-DNILMF |
Integrated logistic matrix factorization |
Drug Target Interaction (DTI) |
https://github.com/LJX0326/Ro-DNILMF.git |
NA |
NA |
NA |
NA |
NA |
NA |
36014371 |
Molecules |
2022 |
| 124 |
50.3 |
1787 |
KEGG |
Drug, Target |
Drug: chemical structure, target: protein sequence |
Ro-DNILMF |
Integrated logistic matrix factorization |
Drug Target Interaction (DTI) |
https://github.com/LJX0326/Ro-DNILMF.git |
NA |
NA |
NA |
NA |
NA |
NA |
36014371 |
Molecules |
2022 |
| 124 |
50.3 |
1787 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical structure, target: protein sequence |
Ro-DNILMF |
Integrated logistic matrix factorization |
Drug Target Interaction (DTI) |
https://github.com/LJX0326/Ro-DNILMF.git |
NA |
NA |
NA |
NA |
NA |
NA |
36014371 |
Molecules |
2022 |
| 124 |
50.3 |
1787 |
DrugBank |
Drug, Target |
Drug: chemical structure, target: protein sequence |
Ro-DNILMF |
Integrated logistic matrix factorization |
Drug Target Interaction (DTI) |
https://github.com/LJX0326/Ro-DNILMF.git |
NA |
NA |
NA |
NA |
NA |
NA |
36014371 |
Molecules |
2022 |
| 125 |
50.05 |
187 |
BindingDB |
Drug, Target |
Target: Fingerprint |
WES |
Bayesian network and multi-variate kernel approach |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
26155766 |
Sci Rep |
2015 |
| 125 |
50.05 |
187 |
External data |
Drug, Target |
Target: Fingerprint |
WES |
Bayesian network and multi-variate kernel approach |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
26155766 |
Sci Rep |
2015 |
| 126 |
50 |
1343 |
Davis |
Drug, Target |
Drug: (the atom symbol, the number of adjacent atoms, the number of adjacent hydrogens, the implicit value of the atom, and whether the atom is in an aromatic structure), Target: (ASCII character string) |
GraphDTA |
Graph Neural Network (GNN) |
Drug Target binding Affinity (DTA) |
https://github.com/thinng/GraphDTA |
NA |
NA |
NA |
NA |
NA |
NA |
33119053 |
Bioinformatics |
2021 |
| 126 |
50 |
1343 |
KIBA |
Drug, Target |
Drug: (the atom symbol, the number of adjacent atoms, the number of adjacent hydrogens, the implicit value of the atom, and whether the atom is in an aromatic structure), Target: (ASCII character string) |
GraphDTA |
Graph Neural Network (GNN) |
Drug Target binding Affinity (DTA) |
https://github.com/thinng/GraphDTA |
NA |
NA |
NA |
NA |
NA |
NA |
33119053 |
Bioinformatics |
2021 |
| 127 |
49.5 |
1203 |
NA |
Drug, Virus |
NA |
IRNMF (Indicator Regularized non-negative Matrix Factorization) |
Non-negative Matrix Factorization (NMF) |
Drug Virus Association (DVA) |
https://github.com/dukebai/IRNMF |
NA |
NA |
NA |
NA |
NA |
NA |
33584672 |
Front Immunol |
2021 |
| 128 |
49 |
1834 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
ICAN (Interpretable Cross-Attention Network) |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/kuratahiroyuki/ICAN |
NA |
NA |
NA |
NA |
NA |
NA |
36279284 |
PLoS One |
2022 |
| 128 |
49 |
1834 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
ICAN (Interpretable Cross-Attention Network) |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/kuratahiroyuki/ICAN |
NA |
NA |
NA |
NA |
NA |
NA |
36279284 |
PLoS One |
2022 |
| 128 |
49 |
559 |
MULAN |
Drug, Disease, Gene |
Chemical: Extended Connectivity Fingerprint (ECFP), Gene: amino acid sequence |
ANTENNA |
Dual-regularized weighted,Imputed One Class Collaborative Filtering (OCCF) algorithm,Random Walk Restart |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
29993812 |
IEEE/ACM Trans Comput Biol Bioinform |
2018 |
| 128 |
49 |
64 |
Fdataset |
Drug, Disease |
Drug: structure chemical, target, side-effect, Diseases: MeSH terms |
PreDR (Predict Drug Repositioning) |
Support Vector Machine (SVM) |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
24244318 |
PLoS One |
2013 |
| 128 |
49 |
1834 |
BIOSNAP |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
ICAN (Interpretable Cross-Attention Network) |
Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/kuratahiroyuki/ICAN |
NA |
NA |
NA |
NA |
NA |
NA |
36279284 |
PLoS One |
2022 |
| 129 |
48.8 |
1914 |
Hetero-C |
Drug, Target, Gene, Side-effect |
NA |
MHGNN (Metapath-aggregated Heterogeneous Graph Neural Network) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/Zora-LM/MHGNN-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
36592060 |
Brief Bioinform |
2023 |
| 129 |
48.8 |
1914 |
Hetero-A |
Drug, Disease, Target, Side-effect |
NA |
MHGNN (Metapath-aggregated Heterogeneous Graph Neural Network) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/Zora-LM/MHGNN-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
36592060 |
Brief Bioinform |
2023 |
| 129 |
48.8 |
1914 |
Hetero-B |
Drug, Disease, Target, Side-effect |
NA |
MHGNN (Metapath-aggregated Heterogeneous Graph Neural Network) |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
https://github.com/Zora-LM/MHGNN-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
36592060 |
Brief Bioinform |
2023 |
| 130 |
48.35 |
1235 |
dataset 2 |
Drug, Target |
Drug: constitutional, topological, and geometrical descriptors; Target: amino acid, pseudo-amino acid, and CTD (composition, transition, distribution) descriptors |
DTI-SNNFRA |
Shared nearest neighbors and fuzzy-rough approximation |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33606741 |
PLoS One |
2021 |
| 130 |
48.35 |
1235 |
dataset 1 |
Drug, Target |
Drug: constitutional, topological, and geometrical descriptors; Target: amino acid, pseudo-amino acid, and CTD (composition, transition, distribution) descriptors |
DTI-SNNFRA |
Shared nearest neighbors and fuzzy-rough approximation |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33606741 |
PLoS One |
2021 |
| 131 |
47.5 |
1795 |
NA |
Drug, Disease, Target, Side-effect, Substructure |
NA |
MGATRx |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://github.com/yellajaswanth/MGATRx |
NA |
NA |
NA |
NA |
NA |
NA |
34014830 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 132 |
47 |
723 |
Yamanishi_NR |
Drug, Target |
NA |
SPLCMF (Self-paced learning with collaborative matrix factorization) |
Matrix Factorization |
Drug Target Interaction (DTI) |
https://github.com/Macau-LYXia/SPLCMF-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
31260620 |
J Chem Inf Model |
2019 |
| 132 |
47 |
723 |
Kuang's dataset |
Drug, Target |
NA |
SPLCMF (Self-paced learning with collaborative matrix factorization) |
Matrix Factorization |
Drug Target Interaction (DTI) |
https://github.com/Macau-LYXia/SPLCMF-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
31260620 |
J Chem Inf Model |
2019 |
| 132 |
47 |
723 |
Yamanishi_E |
Drug, Target |
NA |
SPLCMF (Self-paced learning with collaborative matrix factorization) |
Matrix Factorization |
Drug Target Interaction (DTI) |
https://github.com/Macau-LYXia/SPLCMF-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
31260620 |
J Chem Inf Model |
2019 |
| 132 |
47 |
723 |
Yamanishi_IC |
Drug, Target |
NA |
SPLCMF (Self-paced learning with collaborative matrix factorization) |
Matrix Factorization |
Drug Target Interaction (DTI) |
https://github.com/Macau-LYXia/SPLCMF-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
31260620 |
J Chem Inf Model |
2019 |
| 132 |
47 |
723 |
Yamanishi_GPCR |
Drug, Target |
NA |
SPLCMF (Self-paced learning with collaborative matrix factorization) |
Matrix Factorization |
Drug Target Interaction (DTI) |
https://github.com/Macau-LYXia/SPLCMF-DTI |
NA |
NA |
NA |
NA |
NA |
NA |
31260620 |
J Chem Inf Model |
2019 |
| 133 |
46.75 |
2132 |
DNdataset |
Drug, Disease |
NA |
IDDI-DNN |
Convolutional Neural Network (CNN) |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
37993777 |
BMC Bioinformatics |
2023 |
| 133 |
46.75 |
2132 |
Fdataset |
Drug, Disease |
NA |
IDDI-DNN |
Convolutional Neural Network (CNN) |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
37993777 |
BMC Bioinformatics |
2023 |
| 134 |
46.7 |
1221 |
PMID: 24551427 |
Drug, Target, Side-effect |
Drug(structure, target, side-effect) |
IntegratedSim |
Similarity-fusion methods |
Drug Drug Interaction (DDI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33557749 |
BMC Bioinformatics |
2021 |
| 134 |
46.7 |
1221 |
NDF-RT |
Drug, Disease |
NA |
IntegratedSim |
Similarity-fusion methods |
Drug Drug Interaction (DDI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33557749 |
BMC Bioinformatics |
2021 |
| 135 |
46.56 |
1658 |
Yamanishi_E |
Drug, Target |
NA |
IMCHGAN (Inductive Matrix Completion with Heterogeneous Graph Attention Network) |
Graph Attention Network (GAT),Inductive Matrix Completion (IMC) |
Drug Target Interaction (DTI) |
https://github.com/ljatynu/IMCHGAN/ |
NA |
NA |
NA |
NA |
NA |
NA |
34115592 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 135 |
46.56 |
1658 |
Yamanishi_IC |
Drug, Target |
NA |
IMCHGAN (Inductive Matrix Completion with Heterogeneous Graph Attention Network) |
Graph Attention Network (GAT),Inductive Matrix Completion (IMC) |
Drug Target Interaction (DTI) |
https://github.com/ljatynu/IMCHGAN/ |
NA |
NA |
NA |
NA |
NA |
NA |
34115592 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 135 |
46.56 |
1658 |
Yamanishi_GPCR |
Drug, Target |
NA |
IMCHGAN (Inductive Matrix Completion with Heterogeneous Graph Attention Network) |
Graph Attention Network (GAT),Inductive Matrix Completion (IMC) |
Drug Target Interaction (DTI) |
https://github.com/ljatynu/IMCHGAN/ |
NA |
NA |
NA |
NA |
NA |
NA |
34115592 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 135 |
46.56 |
1658 |
Yamanishi_NR |
Drug, Target |
NA |
IMCHGAN (Inductive Matrix Completion with Heterogeneous Graph Attention Network) |
Graph Attention Network (GAT),Inductive Matrix Completion (IMC) |
Drug Target Interaction (DTI) |
https://github.com/ljatynu/IMCHGAN/ |
NA |
NA |
NA |
NA |
NA |
NA |
34115592 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 135 |
46.56 |
1658 |
DTI-HN |
Drug, Disease, Target, Side-effect |
NA |
IMCHGAN (Inductive Matrix Completion with Heterogeneous Graph Attention Network) |
Graph Attention Network (GAT),Inductive Matrix Completion (IMC) |
Drug Target Interaction (DTI) |
https://github.com/ljatynu/IMCHGAN/ |
NA |
NA |
NA |
NA |
NA |
NA |
34115592 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 136 |
45 |
1220 |
NA |
Drug, Disease, Gene |
NA |
SAveRUNNER (Searching off-lAbel dRUg aNd NEtwoRk) |
Bi-Random walk-based algorithm |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33544720 |
PLoS Comput Biol |
2021 |
| 137 |
44.5 |
1851 |
DRKG |
Drug, Disease, Gene, Anatomies |
NA |
GDRnet |
Graph Neural Network (GNN) |
Drug Disease Association (DDA) |
https://github.com/siddhant-doshi/GDRnet |
Case studies |
NA |
NA |
NA |
NA |
NA |
36228466 |
Comput Biol Med |
2022 |
| 138 |
44 |
1886 |
Fdataset |
Drug, Disease |
NA |
NMFDR (Neural Metric Factorization model for computational Drug Repositioning) |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
35061591 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 138 |
44 |
1886 |
Cdataset |
Drug, Disease |
NA |
NMFDR (Neural Metric Factorization model for computational Drug Repositioning) |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
35061591 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 138 |
44 |
1886 |
DNdataset |
Drug, Disease |
NA |
NMFDR (Neural Metric Factorization model for computational Drug Repositioning) |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
35061591 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 138 |
44 |
1550 |
Luo's dataset |
Drug, Disease, Target, Side-effect |
NA |
KGE_NFM |
Neural Factorization Machine (NFM) |
Drug Target Interaction (DTI) |
https://zenodo.org/record/5500305 |
NA |
NA |
NA |
NA |
NA |
NA |
34811351 |
Nat Commun |
2021 |
| 139 |
42.5 |
1935 |
LL |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 139 |
42.5 |
1935 |
DisGeNET (DGN) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 139 |
42.5 |
1935 |
SLAMS |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 139 |
42.5 |
1935 |
MalaCards (MC) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 139 |
42.5 |
1935 |
RepoDB (RDB) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 139 |
42.5 |
1935 |
DrugBank |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 139 |
42.5 |
1935 |
iDrug (ID) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 140 |
42.4 |
465 |
NA |
Drug, Target, Gene, Side-effect |
Drug: Chemical structure, target, Gene, side-effect |
NA |
Growing Self Organizing Map (GSOM) |
Drug Drug Interaction (DDI) |
https://github.com/fathimanush786/two_tiered_clustrering_data |
NA |
NA |
NA |
NA |
NA |
NA |
29642848 |
BMC Bioinformatics |
2018 |
| 141 |
41.66 |
1473 |
Yamanishi_E |
Drug, Target |
NA |
DTI-HeNE (DTI based on Heterogeneous Network Embedding) |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/arantir123/DTI-hene/ |
NA |
NA |
NA |
NA |
NA |
NA |
34479477 |
BMC Bioinformatics |
2021 |
| 141 |
41.66 |
1473 |
Olayan RS |
Drug, Target |
NA |
DTI-HeNE (DTI based on Heterogeneous Network Embedding) |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/arantir123/DTI-hene/ |
NA |
NA |
NA |
NA |
NA |
NA |
34479477 |
BMC Bioinformatics |
2021 |
| 141 |
41.66 |
1473 |
Yamanishi_IC |
Drug, Target |
NA |
DTI-HeNE (DTI based on Heterogeneous Network Embedding) |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/arantir123/DTI-hene/ |
NA |
NA |
NA |
NA |
NA |
NA |
34479477 |
BMC Bioinformatics |
2021 |
| 141 |
41.66 |
1473 |
Yamanishi_GPCR |
Drug, Target |
NA |
DTI-HeNE (DTI based on Heterogeneous Network Embedding) |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/arantir123/DTI-hene/ |
NA |
NA |
NA |
NA |
NA |
NA |
34479477 |
BMC Bioinformatics |
2021 |
| 141 |
41.66 |
1473 |
Yamanishi_NR |
Drug, Target |
NA |
DTI-HeNE (DTI based on Heterogeneous Network Embedding) |
Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/arantir123/DTI-hene/ |
NA |
NA |
NA |
NA |
NA |
NA |
34479477 |
BMC Bioinformatics |
2021 |
| 142 |
40.7 |
1307 |
NA |
Drug, Target |
Drug: 2-D structural representations, |
CSConv2d |
Convolutional Block Attention Module (CBAM) |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
33925310 |
Biomolecules |
2021 |
| 143 |
40.5 |
142 |
NA |
Drug, Disease, Gene |
NA |
NA |
Matrix Factorization |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
26078775 |
Comput Math Methods Med |
2015 |
| 144 |
39.2 |
154 |
NA |
Drug |
Drug: chemical structure |
NA |
Markov Clustering |
Drug Drug Interaction (DDI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
24934184 |
Chem Biol Drug Des |
2015 |
| 145 |
38.4 |
1444 |
CAS Biomedical Knowledge Graph(COVID-19) |
Disease, Gene, Pathway, Virus, Side-effect, Clinical Trial, Small molecule, Molecular Function |
NA |
NA |
A computer algorithm-driven drug-ranking method |
Drug Disease Association (DDA) |
NA |
Special studies |
COVID-19 |
NA |
NA |
NA |
Top 50 drugs |
34297570 |
J Chem Inf Model |
2021 |
| 146 |
38 |
50 |
STITCH |
Drug, Target |
NA |
RBM model |
Restricted Boltzmann Machine |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
23812976 |
Bioinformatics |
2013 |
| 146 |
38 |
50 |
MATADOR |
Drug, Target |
NA |
RBM model |
Restricted Boltzmann Machine |
Drug Target Interaction (DTI) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
23812976 |
Bioinformatics |
2013 |
| 147 |
37.8 |
328 |
MATADOR |
Drug, Target |
Drug: pubchem ID, Target: target ID(MeSH, STRING 7) |
NA |
Common Neighbours,Jaccard Index,Preferential Attachment,Katz Index |
Drug Target Interaction (DTI) |
http://www.cl.cam.ac.uk/~yg244/16bioinfo |
NA |
NA |
NA |
NA |
NA |
NA |
28095781 |
BMC Bioinformatics |
2017 |
| 148 |
37.65 |
896 |
SMDC |
Drug |
Drug: drug perturbation gene expression level, structural fingerprint and physicochemical property |
DAMT-Model |
Convolutional Neural Network (CNN),Domain-adversarial learning,Bidirectional LSTM (Bi-LSTM) |
Drug Disease Association (DDA) |
https://github.com/JohnnyY8/DAMT-Model |
NA |
NA |
NA |
NA |
NA |
NA |
31999334 |
Bioinformatics |
2020 |
| 148 |
37.65 |
896 |
FD dataset |
Drug |
Drug: drug perturbation gene expression level, structural fingerprint and physicochemical property |
DAMT-Model |
Convolutional Neural Network (CNN),Domain-adversarial learning,Bidirectional LSTM (Bi-LSTM) |
Drug Disease Association (DDA) |
https://github.com/JohnnyY8/DAMT-Model |
NA |
NA |
NA |
NA |
NA |
NA |
31999334 |
Bioinformatics |
2020 |
| 149 |
30.5 |
604 |
Yamanishi |
Drug, Disease, Target |
NA |
Heter-LP |
Label Propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
30547450 |
Methods Mol Biol |
2019 |
| 150 |
27.6 |
1110 |
NA |
Drug, Disease, Gene, Pathway, Side-effect |
NA |
NA |
Support Vector Machine (SVM),Decision Tree (DT),Random Forest (RF) |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
NA |
NA |
32674665 |
Health Informatics J |
2020 |