| 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 |
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 |
| 3 |
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 |
| 4 |
81 |
2099 |
NA |
Drug, Disease, Target, Side-effect |
Drug: SMILES, Target: the amino acid sequences |
MOVE |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/scu-kdde/Bioinfo-MOVE2.0 |
Case studies |
COVID-19 |
Peroxisome proliferator-activated receptor gamma(P37231), Peroxisome proliferator-activated receptor alpha(Q07869), Apoptosis regulator Bcl-2(P10415), Angiotensin-converting enzyme 2(Q9BYF1), Cystic fibrosis transmembrane conductance regulator(P13569), Nuclear receptor subfamily 1 group I member 2(O75469), Annexin A1(P04083) |
NA |
NA |
Top 7 drugs |
37586602 |
Methods |
2023 |
| 5 |
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 |
| 6 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 7 |
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 |
| 8 |
77.875 |
2079 |
Davis |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 8 |
77.875 |
2079 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 8 |
77.875 |
2079 |
DrugBank (version 5.1.9) |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 8 |
77.875 |
2079 |
KIBA |
Drug, Target |
Drug: SMILES, Target: the amino acid sequences |
MULGA (Multi-view Learning and Graph Autoencoder framework) |
Multi-view Learning and Graph Autoencoder (GAE) |
Drug Target Interaction (DTI) |
https://github.com/jianiM/MULGA |
Case studies |
COVID-19 |
Spike glycoprotein |
NA |
NA |
Top 20 drugs |
37610353 |
Bioinformatics |
2023 |
| 9 |
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 |
| 10 |
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 |
| 11 |
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 |
| 11 |
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 |
| 12 |
76.4 |
1394 |
DTINet |
Drug, Disease, Target, Side-effect |
Drug: structure, Target: sequence |
LUNAR |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
COVID-19 |
Tumor necrosis factor |
NA |
NA |
Top 10 drugs |
34081583 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 12 |
76.4 |
1394 |
DTINet |
Drug, Disease, Target, Side-effect |
Drug: structure, Target: sequence |
LUNAR |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
COVID-19 |
Nterleukin-l beta |
NA |
NA |
Top 5 drugs |
34081583 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 12 |
76.4 |
1394 |
DTINet |
Drug, Disease, Target, Side-effect |
Drug: structure, Target: sequence |
LUNAR |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
COVID-19 |
ACE2 |
NA |
NA |
Top 8 drugs |
34081583 |
IEEE/ACM Trans Comput Biol Bioinform |
2021 |
| 13 |
76.3 |
2145 |
Davis |
Drug, Target |
Drug: SMILES, Target: The amino acid Sequence. |
MdDTI |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/lhhu1999/MdDTI |
Case studies |
COVID-19 |
SARS-CoV-2 3C-like protease |
NA |
NA |
Top 5 drugs |
37844375 |
Comput Biol Chem |
2023 |
| 13 |
76.3 |
2145 |
KIBA |
Drug, Target |
Drug: SMILES, Target: The amino acid Sequence. |
MdDTI |
Multi Layer Perception (MLP) |
Drug Target Interaction (DTI) |
https://github.com/lhhu1999/MdDTI |
Case studies |
COVID-19 |
SARS-CoV-2 3C-like protease |
NA |
NA |
Top 5 drugs |
37844375 |
Comput Biol Chem |
2023 |
| 14 |
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 |
| 14 |
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 |
| 14 |
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 |
| 14 |
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 |
| 14 |
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 |
| 15 |
75.8 |
308 |
Positive dataset |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
dtipred |
Random Forest (RF) |
Drug Target Interaction (DTI) |
http://bioinformatics.ua.pt/software/dtipred/ |
Case studies |
Methicillin-resistant Staphylococcus aureus |
(DNA-directed RNA polymerase subunit alpha_Q5HDY4, 30S ribosomal protein S12_Q5HID0, DNA-directed RNA polymerase subunit beta_Q5HID3, Accessory Sec system protein translocase subunit SecY2_Q5HCP4, 30S ribosomal protein S15_Q5HGF8, Elongation factor G_Q5HIC8, 50S ribosomal protein L22_Q5HDW3, 30S ribosomal protein S3_Q5HDW4, 50S ribosomal protein L13_Q5HDZ0, 50S ribosomal protein L25_Q5HIH4) |
NA |
NA |
Top 5 drugs |
27893735 |
PLoS Comput Biol |
2016 |
| 15 |
75.8 |
308 |
Negative dataset |
Drug, Target |
Drug: SMILES, Target: The primary sequence |
dtipred |
Random Forest (RF) |
Drug Target Interaction (DTI) |
http://bioinformatics.ua.pt/software/dtipred/ |
Case studies |
Methicillin-resistant Staphylococcus aureus |
(DNA-directed RNA polymerase subunit alpha_Q5HDY4, 30S ribosomal protein S12_Q5HID0, DNA-directed RNA polymerase subunit beta_Q5HID3, Accessory Sec system protein translocase subunit SecY2_Q5HCP4, 30S ribosomal protein S15_Q5HGF8, Elongation factor G_Q5HIC8, 50S ribosomal protein L22_Q5HDW3, 30S ribosomal protein S3_Q5HDW4, 50S ribosomal protein L13_Q5HDZ0, 50S ribosomal protein L25_Q5HIH4) |
NA |
NA |
Top 5 drugs |
27893735 |
PLoS Comput Biol |
2016 |
| 16 |
75.6 |
894 |
Training Data-(DrugBank (v4.3), TTD, PharmGKB) |
Drug, Disease, Target , Side-effect |
Drug: SMILES, targets: Uniprot ID |
AOPEDF (Arbitrary-Order Proximity Embedded Deep Forest) |
Deep Forest Classifier |
Drug Target Interaction (DTI) |
https://github.com/ChengF-Lab/AOPEDF |
Case studies |
Substance abuse disorder |
G-protein-coupled receptors (GPCRs) |
NA |
NA |
Top 20 drugs |
31971579 |
Bioinformatics |
2020 |
| 16 |
75.6 |
894 |
Validations-DrugCentral |
Drug, Target |
Drug: SMILES, targets: Uniprot ID |
AOPEDF (Arbitrary-Order Proximity Embedded Deep Forest) |
Deep Forest Classifier |
Drug Target Interaction (DTI) |
https://github.com/ChengF-Lab/AOPEDF |
Case studies |
Substance abuse disorder |
G-protein-coupled receptors (GPCRs) |
NA |
NA |
Top 20 drugs |
31971579 |
Bioinformatics |
2020 |
| 16 |
75.6 |
894 |
Validations-ChEMBL |
Drug, Target |
Drug: SMILES, targets: Uniprot ID |
AOPEDF (Arbitrary-Order Proximity Embedded Deep Forest) |
Deep Forest Classifier |
Drug Target Interaction (DTI) |
https://github.com/ChengF-Lab/AOPEDF |
Case studies |
Substance abuse disorder |
G-protein-coupled receptors (GPCRs) |
NA |
NA |
Top 20 drugs |
31971579 |
Bioinformatics |
2020 |
| 17 |
74.3 |
694 |
NA |
Drug, Target |
Drug: Chemical structure, Target: target sequence |
LASSO |
Deep Neural Network (DNN) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Breast Cancer |
NA |
NA |
NA |
Top 5 drugs |
30939415 |
Comput Biol Chem |
2019 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 18 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 19 |
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 |
| 20 |
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 |
| 20 |
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 |
| 21 |
72.3 |
1765 |
Human |
Drug, Target |
Drug: SMILES, Target: binding site |
AttentionSiteDTI |
Bidirectional Long Short-Term Memory (Bi-LSTM),Graph Convolutional Network (GCN),Multi-Layer Perceptron (MLP) |
Drug Target Interaction (DTI) |
https://github.com/yazdanimehdi/AttentionSiteDTI |
Case studies |
COVID-19 |
SARS-CoV-2 |
NA |
NA |
Top 7 drugs |
35817396 |
Brief Bioinform |
2022 |
| 21 |
72.3 |
1765 |
BindingDB |
Drug, Target |
Drug: SMILES, Target: binding site |
AttentionSiteDTI |
Bidirectional Long Short-Term Memory (Bi-LSTM),Graph Convolutional Network (GCN),Multi-Layer Perceptron (MLP) |
Drug Target Interaction (DTI) |
https://github.com/yazdanimehdi/AttentionSiteDTI |
Case studies |
COVID-19 |
SARS-CoV-2 |
NA |
NA |
Top 7 drugs |
35817396 |
Brief Bioinform |
2022 |
| 21 |
72.3 |
1765 |
DUD-E |
Drug, Target |
Drug: SMILES, Target: binding site |
AttentionSiteDTI |
Bidirectional Long Short-Term Memory (Bi-LSTM),Graph Convolutional Network (GCN),Multi-Layer Perceptron (MLP) |
Drug Target Interaction (DTI) |
https://github.com/yazdanimehdi/AttentionSiteDTI |
Case studies |
COVID-19 |
SARS-CoV-2 |
NA |
NA |
Top 7 drugs |
35817396 |
Brief Bioinform |
2022 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 22 |
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 |
| 23 |
70.4 |
2046 |
aBiofilm |
Drug |
Drug: SMILES, |
Anti-Biofilm |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
https://bioinfo.imtech.res.in/manojk/antibiofilm/ |
Case studies |
Antimicrobial resistance |
biofilm |
NA |
NA |
Top 25 drugs |
37356913 |
J Mol Biol |
2023 |
| 23 |
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 |
| 23 |
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 |
| 23 |
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 |
| 23 |
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 |
| 24 |
69.4 |
1769 |
NA |
Drug, Target, Pathway |
NA |
MSDF-CNN |
Graph Convolutional Network (GCN) |
Drug Target Interaction (DTI) |
https://github.com/lemonfino/MSDF-CNN |
Special studies |
Parkinson’s Disease (PD) |
HTR2A |
NA |
NA |
Top 10 drugs |
35897954 |
Molecules |
2022 |
| 25 |
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 |
| 26 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
66.2 |
386 |
Yamanishi_IC |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 27 |
66.2 |
386 |
Yamanishi_E |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
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 |
| 27 |
66.2 |
386 |
Yamanishi_NR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 27 |
66.2 |
386 |
Yamanishi_GPCR |
Drug, Target |
Drug: molecule, Target: target sequence |
PUDTI |
Support Vector Machine (SVM) |
Drug Target Interaction (DTI) |
NA |
Case studies |
Alzheimer's Disease (AD) |
(D(1A), D(2) and D3 dopamine receptors (P21728, P14416 and P35462), alpha-1A and alpha-1B adrenergic receptor (P35348 and P35368), 5-hydroxytryptamine receptors (P28223) and potassium voltage-gated channel subfamily H member 2(Q12809) |
NA |
NA |
NA |
28808275 |
Sci Rep |
2017 |
| 27 |
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 |
| 27 |
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 |
| 28 |
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 |
| 29 |
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 |
| 30 |
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 |
| 31 |
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 |
| 31 |
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 |
| 32 |
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 |
| 32 |
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 |
| 33 |
63.2 |
356 |
Yamanishi_GPCR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 33 |
63.2 |
356 |
Yamanishi_NR |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 33 |
63.2 |
356 |
NA |
Drug, Disease, Target |
NA |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 33 |
63.2 |
356 |
Yamanishi_E |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 33 |
63.2 |
356 |
Yamanishi_IC |
Drug, Target |
Drug: chemical sturcture, Target: target sequence |
Heter-LP |
Heterogeneous label propagation |
Drug Target Interaction (DTI),Drug Disease Association (DDA) |
NA |
Case studies |
Osteoarthritis with mild chondrodysplasia |
NA |
NA |
NA |
2 drugs |
28300647 |
J Biomed Inform |
2017 |
| 34 |
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 |
| 35 |
61.8 |
1096 |
NA |
Drug, Target |
Drug: SMILES, Target: sequence |
DLDTI |
Representation learning,Convolutional Neural Network (CNN) |
Drug Target Interaction (DTI) |
https://github.com/CUMTzackGit/DLDTI |
Case studies |
Atherosclerosis |
NA |
Tetramethylpyrazine |
NA |
288 targets |
33187537 |
J Transl Med |
2020 |
| 36 |
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 |
| 36 |
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 |
| 36 |
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 |
| 36 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 37 |
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 |
| 38 |
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 |
| 38 |
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 |
| 38 |
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 |
| 38 |
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 |
| 38 |
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 |
| 38 |
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 |
| 38 |
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 |
| 38 |
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 |
| 39 |
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 |
| 39 |
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 |
| 39 |
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 |
| 39 |
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 |
| 39 |
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 |
| 40 |
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 |
| 41 |
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 |
| 41 |
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 |
| 41 |
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 |
| 42 |
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 |
| 42 |
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 |
| 42 |
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 |
| 42 |
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 |
| 42 |
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 |
| 43 |
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 |
| 44 |
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 |
| 45 |
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 |
| 45 |
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 |
| 45 |
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 |
| 45 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 46 |
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 |
| 47 |
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 |
| 47 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 48 |
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 |
| 49 |
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 |
| 49 |
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 |
| 49 |
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 |
| 50 |
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 |
| 50 |
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 |
| 51 |
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 |
| 51 |
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 |
| 52 |
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 |
| 52 |
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 |
| 52 |
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 |
| 52 |
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 |
| 52 |
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 |
| 52 |
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 |
| 53 |
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 |
| 53 |
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 |
| 54 |
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 |
| 54 |
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 |
| 54 |
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 |
| 55 |
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 |
| 55 |
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 |
| 55 |
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 |
| 56 |
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 |
| 56 |
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 |
| 57 |
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 |
| 57 |
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 |
| 57 |
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 |
| 57 |
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 |
| 57 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 58 |
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 |
| 59 |
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 |
| 60 |
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 |
| 60 |
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 |
| 60 |
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 |
| 60 |
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 |
| 60 |
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 |
| 61 |
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 |
| 62 |
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 |
| 62 |
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 |
| 63 |
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 |
| 64 |
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 |