MultiCASE Platform for In Silico Toxicology-Reference-Cited by-同舟云学术

MultiCASE Platform for In Silico Toxicology

Published:2022 Issue: Volume: Page:497-518
ISSN:1064-3745
Container-title:Methods in Molecular Biology
language:
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Author:

Chakravarti Suman K.,Saiakhov Roustem D.

Publisher

Springer US

Link

https://link.springer.com/content/pdf/10.1007/978-1-0716-1960-5_19

Reference61 articles.

1. Klopman G (1984) Artificial intelligence approach to structure-activity studies. Computer automated structure evaluation of biological activity of organic molecules. J Am Chem Soc 106(24):7315–7321

2. Klopman G, Fercu D (1994) Application of the multiple computer automated structure evaluation methodology to a quantitative structure-activity relationship study of acidity. J Comp Chem 15(9):1041–1050

3. Chakravarti S, Klopman G, Ivanov J et al (2005) MC4PC—an artificial intelligence approach to the discovery of quantitative structure–toxic activity relationships. In: Helma C (ed) Predictive toxicology, 1st edn. CRC Press, Boca Raton

4. Chakravarti S, Saiakhov R, Klopman G (2012) Optimizing predictive performance of CASE ultra expert system models using the applicability domains of individual toxicity alerts. J Chem Inf Model 52(10):2609–2618. https://doi.org/10.1021/ci300111r

5. Chakravarti S, Alla SRM (2019) Descriptor free QSAR modeling using deep learning with long short-term memory neural networks. Front Artif Intell 6(2):17. https://doi.org/10.3389/frai.2019.00017

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