Target Interaction Representation
Target Interaction Representation is a computational framework that specifies the formal modeling of molecular interactions between pharmacological agents and their biological targets, distinguished by its structured encoding of binding relationships, functional effects, and contextual conditions within drug knowledge systems.
18
Publications
1.6K
Citations
68
Authors
34
Institutions
Publications per year
2017–2026
14
18
MolTrans: Molecular Interaction Transformer for drug–target interaction prediction
Kexin Huang, Cao Xiao, Lucas M. Glass et al. · Bioinformatics · 2020 · 604 citations · Full text
Interpretable Drug Target Prediction Using Deep Neural Representation
Kyle Yingkai Gao, Achille Fokoue, Heng Luo et al. · 2018 · 248 citations · Full text
Effective drug–target interaction prediction with mutual interaction neural network
Fei Li, Ziqiao Zhang, Jihong Guan et al. · Bioinformatics · 2022 · 82 citations · Full text
Pharmacy, Pharmacology, Drug Design +16
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34

Central South University
Changsha, China
2 h-index
12 publications
559 citations
University at Buffalo, State University of New York
Buffalo, United States
1 h-index
2 publications
128 citations

Gachon University
Seongnam-si, South Korea
1 h-index
3 publications
87 citations

Babeș-Bolyai University
Cluj-Napoca, Romania
1 h-index
2 publications
34 citations
IBM (United States)
Armonk, United States
1 h-index
6 publications
1.5K citations

Sichuan University
Chengdu, China
1 h-index
3 publications
333 citations
Danaher (China)
Shanghai, China
1 h-index
1 publications
64 citations
University of Illinois Urbana-Champaign
Urbana, United States
1 h-index
1 publications
604 citations
1–8 of 34
3 publications · 729 citations
3
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2 publications · 76 citations
2
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2 publications · 142 citations
2
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Repository · 2 publications · 121 citations
2
h-index
PNS · 1 publications · 24 citations
1
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1–5