Exploring Multi-level Mutual Information for Drug-target Interaction Prediction
Author:
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9312958/9312977/09313395.pdf?arnumber=9313395
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Cross-view contrastive representation learning approach to predicting DTIs via integrating multi-source information;Methods;2023-10
2. MOVE: Integrating Multi-source Information for Predicting DTI via Cross-view Contrastive Learning;2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2022-12-06
3. A heterogeneous network-based method with attentive meta-path extraction for predicting drug–target interactions;Briefings in Bioinformatics;2022-06-01
4. Identifying drug–target interactions via heterogeneous graph attention networks combined with cross-modal similarities;Briefings in Bioinformatics;2022-02-26
5. Predicting Drug-target Interaction Via Self-supervised Learning;IEEE/ACM Transactions on Computational Biology and Bioinformatics;2022
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