| 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 |
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 |
| 2 |
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 |
| 3 |
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 |
| 4 |
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 |
| 4 |
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 |
| 4 |
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 |
| 5 |
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 |
| 6 |
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 |
| 7 |
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 |
