| 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 |
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 |
| 1 |
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 |
| 1 |
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 |
| 1 |
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 |
| 1 |
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 |
| 1 |
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 |
| 1 |
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 |
| 2 |
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 |
| 3 |
73.7 |
1366 |
NA |
Drug, Target |
Molecular descriptors |
NA |
Random Forest (RF) |
Drug Disease Association (DDA) |
https://github.com/sblab/DTN |
Special studies |
Hyperlipidemia |
NA |
NA |
NA |
Top 9 drugs |
34030115 |
Comput Biol Chem |
2021 |
| 4 |
72.95 |
2134 |
External Set-1 |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 4 |
72.95 |
2134 |
External Set-2 |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 4 |
72.95 |
2134 |
DRH |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 4 |
72.95 |
2134 |
NA |
Drug |
Drug: SMILES |
NA |
Graph Attention Network (GAT),Graph Isomorphism Network (GIN) |
Drug Target binding Affinity (DTA) |
NA |
Special studies |
COVID-19 |
SARS-CoV-2 main protease (Mpro) |
NA |
NA |
Top 10 drugs |
37960886 |
J Chem Inf Model |
2023 |
| 5 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 6 |
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 |
| 7 |
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 |
| 8 |
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 |
| 8 |
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 |
| 9 |
68.5 |
672 |
NA |
Gene, Celllines |
NA |
NA |
Deep neural Network (DNN),Support Vector Machine (SVM),Random Forest (RF),Gradient Boosted Machine with trees (GBM),logistic regression with elastic net regularization (EN) |
Drug Disease Association (DDA) |
NA |
Special studies |
Depressive Disorder |
NA |
NA |
NA |
Top 8 drugs |
30010603 |
IEEE J Biomed Health Inform |
2019 |
| 9 |
68.5 |
672 |
NA |
Gene, Celllines |
NA |
NA |
Deep neural Network (DNN),Support Vector Machine (SVM),Random Forest (RF),Gradient Boosted Machine with trees (GBM),logistic regression with elastic net regularization (EN) |
Drug Disease Association (DDA) |
NA |
Special studies |
Schizophrenia |
NA |
NA |
NA |
Top 8 drugs |
30010603 |
IEEE J Biomed Health Inform |
2019 |
| 10 |
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 |
| 11 |
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 |
| 12 |
64.8 |
1814 |
NA |
Drug, chemical |
NA |
NA |
Knowledge Graph Embedding |
Drug Disease Association (DDA) |
NA |
Special studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 10 drugs |
36180861 |
BMC Bioinformatics |
2022 |
| 13 |
64.6 |
2116 |
NA |
Drug |
Drug: SMILES |
NA |
Graph Convolutional Network (GCN),XGBoost |
Drug Target Interaction (DTI) |
NA |
Special studies |
Parkinson’s Disease (PD) |
PINK1 (Phosphatase and Tensin homologue-induced kinase 1) |
NA |
NA |
Top 22 drugs |
37544165 |
Comput Methods Programs Biomed |
2023 |
| 14 |
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 |
| 14 |
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 |
| 14 |
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 |
| 15 |
58.7 |
725 |
NA |
Drug, Disease, Target |
Drug: drug-target target |
NA |
CLASH (Complementary Linkage with Anchoring and Scoring),Graph-based Semi-Supervised Learning (SSL) |
Drug Drug Interaction (DDI) |
NA |
Case studies |
Vascular dementia |
NA |
NA |
NA |
Top 11 drug |
31337333 |
BMC Bioinformatics |
2019 |
| 16 |
58.5 |
1322 |
NA |
Drug, Gene |
NA |
NA |
Deep Autoencoder,XGBoost |
Drug Target Interaction (DTI) |
https://github.com/tsjshg/ai-drug-dev |
Special studies |
Alzheimer's Disease (AD) |
NA |
NA |
NA |
Top 20 drugs |
33941241 |
Alzheimers Res Ther |
2021 |
| 17 |
55.4 |
1915 |
NA |
Drug, Gene |
NA |
NA |
Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
NA |
Special studies |
Non-Small Cell Lung Cancer (NSCLC) |
NA |
NA |
NA |
Top 11 drugs |
36768566 |
Int J Mol Sci |
2023 |
| 17 |
55.4 |
1915 |
NA |
Drug, Gene |
NA |
NA |
Random Walk with Restart (RWR) |
Drug Disease Association (DDA) |
NA |
Special studies |
Colorectal Cancer |
NA |
NA |
NA |
Top 9 drugs |
36768566 |
Int J Mol Sci |
2023 |
| 18 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Urticaria |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 18 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 18 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Chronic lymphocytic leukemia |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 18 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Dysmenorrhea |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 18 |
50.5 |
569 |
NA |
Drug, Disease, Target |
NA |
NA |
Random Forest (RF),Neural network |
Drug Disease Association (DDA) |
NA |
Case studies |
Psoriasis |
NA |
NA |
NA |
Candidate drugs with the mean AUC>0.9 |
30463505 |
BMC Bioinformatics |
2018 |
| 19 |
42.5 |
1935 |
DisGeNET (DGN) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 19 |
42.5 |
1935 |
LL |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 19 |
42.5 |
1935 |
MalaCards (MC) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 19 |
42.5 |
1935 |
SLAMS |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 19 |
42.5 |
1935 |
RepoDB (RDB) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 19 |
42.5 |
1935 |
iDrug (ID) |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 19 |
42.5 |
1935 |
DrugBank |
Drug, Disease, Gene |
NA |
NA |
Biased random walks |
Drug Disease Association (DDA) |
NA |
Case studies |
Rheumatoid Arthritis |
NA |
NA |
NA |
1 drug |
35839194 |
IEEE/ACM Trans Comput Biol Bioinform |
2023 |
| 20 |
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 |
| 21 |
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 |
| 22 |
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 |
| 23 |
38.4 |
1444 |
CAS Biomedical Knowledge Graph(COVID-19) |
Disease, Gene, Pathway, Virus, Side-effect, Clinical Trial, Small molecule, Molecular Function |
NA |
NA |
A computer algorithm-driven drug-ranking method |
Drug Disease Association (DDA) |
NA |
Special studies |
COVID-19 |
NA |
NA |
NA |
Top 50 drugs |
34297570 |
J Chem Inf Model |
2021 |
| 24 |
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 |
| 25 |
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 |