ADis-QSAR: a machine learning model based on biological activity differences of compounds
Author:
Publisher
Springer Science and Business Media LLC
Subject
Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery
Link
https://link.springer.com/content/pdf/10.1007/s10822-023-00517-1.pdf
Reference47 articles.
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2. Zhu H (2020) Big data and artificial intelligence modeling for drug discovery. Annu Rev Pharmacol 60:573–589. https://doi.org/10.1146/annurev-pharmtox-010919-023324
3. Muhammad U, Uzairu A, Ebuka Arthur D (2018) Review on: quantitative structure activity relationship (QSAR) modeling. https://ijaar.org/articles/Volume4-Number5/Sciences-Technology-Engineering/ijaar-ste-v4n5-may18-p6.pdf. Accessed 19 Apr. 2018
4. Gedeck P, Kramer C, Ertl P (2010) Computational analysis of structure–activity relationships. Prog Med Chem 49:113–160. https://doi.org/10.1016/S0079-6468(10)49004-9
5. Xiong Y, Qiao Y, Kihara D, Zhang H-Y, Zhu X, Wei D-Q (2019) Survey of machine learning techniques for prediction of the isoform specificity of cytochrome P450 substrates. Curr Drug Metab 20(3):229–235. https://doi.org/10.2174/1389200219666181019094526
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