QSAR Anti-HIV Feature Selection and Prediction for Drug Discovery Using Genetic Algorithm and Machine Learning Algorithms-Reference-Cited by-同舟云学术

QSAR Anti-HIV Feature Selection and Prediction for Drug Discovery Using Genetic Algorithm and Machine Learning Algorithms

Published:2022 Issue: Volume: Page:191-204
ISSN:2522-8595
Container-title:EAI/Springer Innovations in Communication and Computing
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Author:

Labjar Houda,Labjar Najoua,Kissi Mohamed

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-77185-0_12

Reference30 articles.

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3. I. Hdoufane, J. Stoycheva, A. Tadjer, D. Villemin, M. Najdoska-Bogdanov, J. Bogdanov, D. Cherqaoui, QSAR and molecular docking studies of indole-based analogs as HIV-1 attachment inhibitors. J. Mol. Struct. 1193, 429–443 (2019)

4. R. Todeschini, V. Consonni, Molecular Descriptors for Chemoinformatics (Wiley-VCH, 2009)

5. M. Eklund, U. Norinder, S. Boyer, L. Carlsson, Choosing feature selection and learning algorithms in QSAR. J. Chem. Inf. Model. 54(3), 837–843 (2014)

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