| 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 |
91.9 |
2042 |
NA |
Drug, Disease, Target |
Drug: SMILES, Target: the amino acid sequences |
VGAEDTI |
Random Forest (RF),Variational Graph AutoEncoder (VGAE),Graph AutoEncoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/FengYinFei/VGAEDTI |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 15 drugs |
37415176 |
BMC Bioinformatics |
2023 |
| 2 |
86.05 |
2168 |
Bdataset |
Drug, Disease, Target |
Drug: SMILES, Disease: MesH, Target: Sequence |
HMLKGAT |
Graph Attention Network (The principle of three degrees influence),Multi-Kernel Learning Method (Gaussian kernel function,Cosine similarity function),Neural network |
Drug Disease Association (DDA) |
https://github.com/LDD-0914/HMLKGAT.git |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 5 diseases |
38051617 |
IEEE/ACM Trans Comput Biol Bioinform |
2024 |
| 2 |
86.05 |
2168 |
Hetero-A |
Drug, Disease, Target |
NA |
HMLKGAT |
Graph Attention Network (The principle of three degrees influence),Multi-Kernel Learning Method (Gaussian kernel function,Cosine similarity function),Neural network |
Drug Disease Association (DDA) |
https://github.com/LDD-0914/HMLKGAT.git |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 5 diseases |
38051617 |
IEEE/ACM Trans Comput Biol Bioinform |
2024 |
| 3 |
85.6 |
2118 |
DTINet |
Drug, Disease, Target |
Drug: SMILES(Drugbank), Target: amino acid sequences(HPRD) |
SATS |
Graph Neural Network (GNN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 30 drugs |
37672364 |
IEEE J Biomed Health Inform |
2023 |
| 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 |
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 |
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 |
| 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 |
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 |
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 |
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 |
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 |
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 |
| 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 |
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 |
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 |
| 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 |
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 |
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 |
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 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
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 |
| 7 |
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 |
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 |
| 8 |
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 |
| 8 |
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 |
| 8 |
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 |
| 8 |
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 |
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 |
| 9 |
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 |
| 9 |
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 |
| 9 |
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 |
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 |
| 10 |
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 |
| 10 |
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 |
| 10 |
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 |
| 10 |
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 |
| 10 |
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 |
| 10 |
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 |
| 10 |
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 |
| 10 |
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 |
| 11 |
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 |
| 11 |
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 |
| 11 |
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 |
| 11 |
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 |
| 11 |
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 |
| 12 |
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 |
| 13 |
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 |
| 13 |
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 |
| 13 |
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 |
| 13 |
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 |
| 13 |
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 |
| 13 |
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 |
| 13 |
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 |
| 13 |
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 |
| 14 |
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 |
| 14 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 15 |
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 |
| 16 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 17 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 20 |
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 |
| 20 |
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 |
| 21 |
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 |
| 21 |
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 |
| 21 |
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 |
| 21 |
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 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 23 |
77.4 |
607 |
DTINet |
Drug, Disease, Target , Side-effect |
Drug: Morgan fingerprints, Target: target sequence |
NeoDTI (NEural integration of neighbOr information for DTI prediction) |
Matrix Factorization |
Drug Target Interaction (DTI) |
https://github.com/FangpingWan/NeoDTI |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 20 predictions |
30561548 |
Bioinformatics |
2019 |
| 24 |
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 |
| 24 |
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 |
| 24 |
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 |
| 24 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 25 |
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 |
| 26 |
76.6 |
1691 |
NA |
Drug, Target |
Drug: SMILES, Target: amino-acid sequences |
NA |
Convolutional Neural Network (CNN),Deep Neural Network (DNN),Random Forest (RF) |
Drug Target Interaction (DTI) |
https://github.com/Shkev/Sars-CoV-2-NSP-Predictions |
Case studies |
NA |
NA |
NA |
Drug target interaction |
13 predictions |
35468672 |
Front Biosci (Landmark Ed) |
2022 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 28 |
76.5 |
1776 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DeepFusion |
Graph Convolutional Network (GCN),Transformer |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 14 predictions |
35219861 |
Methods |
2022 |
| 28 |
76.5 |
1776 |
BIOSNAP |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
DeepFusion |
Graph Convolutional Network (GCN),Transformer |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 14 predictions |
35219861 |
Methods |
2022 |
| 29 |
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 |
| 29 |
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 |
| 29 |
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 |
| 29 |
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 |
| 29 |
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 |
| 29 |
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 |
| 29 |
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 |
| 30 |
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 |
| 30 |
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 |
| 30 |
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 |
| 31 |
73.7 |
1032 |
Fdataset |
Drug, Disease |
Drug: SMILES, Disease: Phenotye |
NEDD |
Random Forest (RF),Random Walk (RW) |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 15 predictions |
32938396 |
BMC Bioinformatics |
2020 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 32 |
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 |
| 33 |
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 |
| 33 |
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 |
| 33 |
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 |
| 33 |
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 |
| 33 |
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 |
| 33 |
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 |
| 33 |
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 |
| 33 |
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 |
| 34 |
72.5 |
741 |
NA |
Drug, Target |
Drug: structure, Target: sequence |
NA |
Low Rank Embedding (LRE) |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 30 predictions |
28541222 |
IEEE/ACM Trans Comput Biol Bioinform |
2019 |
| 34 |
72.5 |
764 |
NA |
Drug, Target |
Drug: structure, Target: sequence |
MCM |
Matrix Completion |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 26 predictions |
31538961 |
IET Syst Biol |
2019 |
| 35 |
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 |
| 35 |
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 |
| 36 |
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 |
| 36 |
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 |
| 36 |
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 |
| 36 |
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 |
| 36 |
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 |
| 36 |
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 |
| 36 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 38 |
70.9 |
1796 |
Zhang's dataset |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
GraphPK (Graph-based Prior Knowledge) |
Multimodal neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 10 predictions |
34375284 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 38 |
70.9 |
1796 |
Zhang's dataset |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
GraphPK (Graph-based Prior Knowledge) |
Multimodal neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 10 predictions |
34375284 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 38 |
70.9 |
1796 |
Amazon's dataset |
Drug, Disease |
Drug: SMILES, Disease: Mesh semantic |
GraphPK (Graph-based Prior Knowledge) |
Multimodal neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 10 predictions |
34375284 |
IEEE/ACM Trans Comput Biol Bioinform |
2022 |
| 39 |
70.4 |
150 |
Yamanishi_IC |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
NA |
Adaptive combination |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 5 predictions |
26543857 |
Biomed Res Int |
2015 |
| 39 |
70.4 |
150 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
NA |
Adaptive combination |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 5 predictions |
26543857 |
Biomed Res Int |
2015 |
| 39 |
70.4 |
150 |
Yamanishi_NR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
NA |
Adaptive combination |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 5 predictions |
26543857 |
Biomed Res Int |
2015 |
| 39 |
70.4 |
150 |
Yamanishi_E |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
NA |
Adaptive combination |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 5 predictions |
26543857 |
Biomed Res Int |
2015 |
| 40 |
70.1 |
789 |
NA |
Drug, Disease |
Drug: SMILES, Diseases: MeSH terms |
NA |
Non-linear computational approach |
Drug Disease Association (DDA) |
http://bioinformatics.aut.ac.ir/drug-disc/ (Data) |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 16 predictions |
31726977 |
BMC Bioinformatics |
2019 |
| 41 |
68.9 |
813 |
Cancer subset |
Drug, Disease, Target |
Drug: chemical structure, Target: the amino acid sequences |
NA |
Tensor decomposition |
Drug Disease Target associations |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 10 predictions |
31839008 |
BMC Bioinformatics |
2019 |
| 41 |
68.9 |
813 |
DTD |
Drug, Disease, Target |
Drug: chemical structure, Target: the amino acid sequences |
NA |
Tensor decomposition |
Drug Disease Target associations |
NA |
Case studies |
NA |
NA |
NA |
Drug target interaction |
Top 10 predictions |
31839008 |
BMC Bioinformatics |
2019 |
| 42 |
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 |
| 42 |
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 |
| 42 |
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 |
| 43 |
68.1 |
467 |
NA |
Drug, Target, Side-effect |
Drug: chemical properties, target targets, side-effect |
NA |
Pareto dominance,Collaborative filtering |
Drug Disease Association (DDA) |
NA |
NA |
NA |
NA |
NA |
Drug disease interaction |
Top 20 predictions |
29649971 |
BMC Bioinformatics |
2018 |
| 44 |
67.3 |
1836 |
NA |
Drug, Target |
Drug: Fingerprint, |
KUALA (Kinase drUgs mAchine Learning frAmework) |
Naïve Bayes (NB),Logistic regression (LR),Support Vector Machine (SVM),Decision Tree (DT),Random Forest (RF),Neural Network (NNet),eXtreme Gradient Boosting (XGBoost),K-Nearest Neighbour (K-NN),Classification and Regression Tree (CART),Least Absolute Shrinkage and Selection Operator (LASSO),Ridge Regression (RIDGE),Elastic net regression (ELNET) |
Drug Target Interaction (DTI) |
https://github.com/molinfrimed/multi-kinases |
Case studies |
NA |
Kinases |
NA |
Drug target interaction |
5 pedictions |
36284125 |
Sci Rep |
2022 |
| 45 |
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 |
| 45 |
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 |
| 45 |
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 |
| 45 |
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 |
| 45 |
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 |
| 45 |
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 |
| 46 |
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 |
| 47 |
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 |
| 47 |
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 |
| 47 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 49 |
65.6 |
573 |
Fdataset |
Drug, Disease |
Drug: chemical substructures, Disease: MeSH |
RLSDR (Regularized Least Square for Drug Repositioning) |
Regularized Least Square |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 19 predictions |
29700660 |
Acta Biotheor |
2018 |
| 49 |
65.6 |
573 |
Fdataset |
Drug, Disease |
Drug: chemical substructures, Disease: MeSH |
RLSDR (Regularized Least Square for Drug Repositioning) |
Regularized Least Square |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 19 predictions |
29700660 |
Acta Biotheor |
2018 |
| 49 |
65.6 |
573 |
DNdataset |
Drug, Disease |
NA |
RLSDR (Regularized Least Square for Drug Repositioning) |
Regularized Least Square |
Drug Disease Association (DDA) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 19 predictions |
29700660 |
Acta Biotheor |
2018 |
| 50 |
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 |
| 51 |
65 |
1396 |
DTINet |
Drug, Disease, Target |
NA |
DDTE |
Graph Embedding Algorithm |
Drug Target Interaction (DTI) |
NA |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
3 predictions |
34119691 |
J Biomed Inform |
2021 |
| 52 |
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 |
| 52 |
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 |
| 53 |
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 |
| 53 |
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 |
| 54 |
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 |
| 54 |
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 |
| 54 |
62.5 |
1072 |
NA |
Drug, Disease, Target, Pathway, Therapeutic classes |
NA |
NMTF (Non-negative Matrix Tri-Factorization) |
Matrix Factorization |
Drug Target Interaction (DTI) |
https://github.com/DEIB-GECO/NMTF-DrugRepositioning |
Case studies |
NA |
NA |
NA |
Drug disease interaction |
Top 5 predictions |
32365039 |
IEEE J Biomed Health Inform |
2020 |
| 55 |
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 |
| 55 |
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 |
| 55 |
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 |
| 55 |
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 |
| 56 |
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 |
| 56 |
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 |
| 57 |
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 |
| 57 |
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 |
| 57 |
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 |
| 57 |
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 |
| 57 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 59 |
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 |
| 59 |
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 |
| 59 |
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 |
| 59 |
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 |
| 59 |
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 |
| 60 |
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 |
| 60 |
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 |
| 60 |
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 |
| 61 |
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 |
| 61 |
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 |
| 62 |
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 |
| 62 |
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 |
| 62 |
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 |
| 62 |
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 |
| 62 |
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 |
| 63 |
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 |
| 63 |
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 |
| 63 |
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 |
| 63 |
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 |
| 63 |
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 |
| 64 |
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 |
| 65 |
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 |
| 65 |
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 |
| 66 |
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 |
| 67 |
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 |
| 67 |
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 |
| 68 |
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 |
| 68 |
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 |
| 68 |
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 |
| 68 |
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 |
| 68 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 69 |
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 |
| 70 |
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 |
| 70 |
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 |
| 71 |
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 |
| 71 |
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 |
| 72 |
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 |
| 72 |
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 |
| 72 |
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 |
| 72 |
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 |
| 73 |
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 |
| 73 |
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 |
| 73 |
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 |
| 74 |
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 |
| 75 |
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 |
| 75 |
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 |
| 76 |
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 |
| 76 |
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 |
| 77 |
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 |
| 77 |
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 |
| 78 |
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 |
| 78 |
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 |
| 78 |
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 |
| 78 |
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 |
| 78 |
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 |
| 78 |
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 |
| 79 |
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 |
| 79 |
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 |
| 80 |
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 |
| 80 |
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 |
| 81 |
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 |
| 82 |
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 |
| 82 |
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 |
| 82 |
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 |
| 82 |
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 |
| 82 |
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 |
| 83 |
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 |
| 83 |
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 |
| 83 |
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 |
| 84 |
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 |
| 84 |
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 |
| 85 |
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 |
| 86 |
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 |
| 86 |
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 |
| 86 |
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 |
| 86 |
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 |
| 86 |
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 |
| 87 |
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 |
| 87 |
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 |
| 88 |
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 |
| 88 |
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 |
| 89 |
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 |
| 89 |
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 |
| 89 |
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 |
| 89 |
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 |
| 89 |
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 |
| 90 |
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 |
| 91 |
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 |
| 92 |
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 |
| 92 |
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 |
| 92 |
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 |
| 92 |
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 |
| 93 |
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 |
| 94 |
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 |
| 94 |
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 |
| 94 |
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 |
| 94 |
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 |
| 94 |
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 |
| 95 |
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 |
| 96 |
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 |
| 97 |
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 |
| 98 |
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 |
| 98 |
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 |
| 99 |
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 |
| 100 |
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 |
| 100 |
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 |
| 101 |
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 |
| 102 |
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 |