Graph-based Inference
Graph-Based Inference is a computational approach within drug repurposing informatics that leverages graph-structured representations of biological and pharmacological data to identify novel therapeutic indications by systematically propagating and inferring relationships among drugs, targets, diseases, and other biomedical entities.
181
Publications
9.5K
Citations
764
Authors
323
Institutions
Publications per year
2017–2026
125
Parents
181
Low Data Drug Discovery with One-Shot Learning
Han Altae-Tran, Bharath Ramsundar, Aneesh Pappu et al. · ACS Central Science · 2017 · 821 citations · Full text
Learning Graphs From Data: A Signal Representation Perspective
Xiaowen Dong, Dorina Thanou, Michael Rabbat et al. · IEEE Signal Processing Magazine · 2019 · 408 citations · Full text
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
Dragomir Anguelov, Ben Taskar, Vassil Chatalbashev et al. · 2005 · 352 citations
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323

Chinese Academy of Sciences
Beijing, China
7 h-index
29 publications
1.8K citations

Peking University
Beijing, China
5 h-index
9 publications
1K citations
Stanford University
Stanford, United States
5 h-index
13 publications
4.7K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
5 h-index
12 publications
306 citations

Central South University
Changsha, China
4 h-index
13 publications
521 citations

Hefei University of Technology
Hefei, China
4 h-index
15 publications
370 citations
University of Oxford
Oxford, United Kingdom
4 h-index
8 publications
803 citations
University of California, Berkeley
Berkeley, United States
4 h-index
4 publications
653 citations
1–8 of 323
Repository · 21 publications · 520 citations
14
h-index
5 publications · 182 citations
5
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5 publications · 159 citations
5
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4 publications · 164 citations
4
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TPAMI · 4 publications · 326 citations
4
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