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Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction. (arXiv:2205.05957v1 [cs.LG])
Web: http://arxiv.org/abs/2205.05957
cs.LG updates on arXiv.org arxiv.org
Illuminating the interconnections between drugs and genes is an important
topic in drug development and precision medicine. Currently, computational
predictions of drug-gene interactions mainly focus on the binding interactions
without considering other relation types like agonist, antagonist, etc. In
addition, existing methods either heavily rely on high-quality domain features
or are intrinsically transductive, which limits the capacity of models to
generalize to drugs/genes that lack external information or are unseen during
the training process. To address these problems, we propose …
arxiv gene learning prediction representation representation learning