Drug repositioning based on residual attention network and free multiscale adversarial training-Reference-Cited by-同舟云学术

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Drug repositioning based on residual attention network and free multiscale adversarial training

Published:2024-08-08 Issue:1 Volume:25 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Li Guanghui,Li Shuwen,Liang Cheng,Xiao Qiu,Luo Jiawei

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangxi Province

Natural Science Foundation of Shandong Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1186/s12859-024-05893-5.pdf

Reference62 articles.

1. Rifaioglu AS, Atas H, Martin MJ, Cetin-Atalay R, Atalay V, Doğan T. Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases. Brief Bioinform. 2019;20(5):1878–912.

2. Ashburn TT, Thor KB. Drug repositioning: identifying and developing new uses for existing drugs. Nat Rev Drug Discov. 2004;3(8):673–83.

3. Dickson M, Gagnon JP. Key factors in the rising cost of new drug discovery and development. Nat Rev Drug Discov. 2004;3(5):417–29.

4. Padhy BM, Gupta YK. Drug repositioning: re-investigating existing drugs for new therapeutic indications. J Postgrad Med. 2011;57(2):153.

5. Xue H, Li J, Xie H, Wang Y. Review of drug repositioning approaches and resources. Int J Biol Sci. 2018;14(10):1232.

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