A novel approach based on deep residual learning to predict drug’s anatomical therapeutic chemical code
Author:
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9312958/9312977/09313327.pdf?arnumber=9313327
Cited by 4 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. Predicting of microbe-drug associations via a pre-completion-based label propagation algorithm;2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2022-12-06
2. SADeepcry: a deep learning framework for protein crystallization propensity prediction using self-attention and auto-encoder networks;Briefings in Bioinformatics;2022-08-29
3. Predicting Anatomical Therapeutic Chemical Drug Classes from 17 molecules’ Properties of Drugs by Multi-Label Binary Relevance Approach with MLSMOTE;2021 5th International Conference on Computational Biology and Bioinformatics;2021-12-26
4. A novel graph attention model for predicting frequencies of drug–side effects from multi-view data;Briefings in Bioinformatics;2021-07-02
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