Effective data-balancing methods for class-imbalanced genotoxicity datasets using machine learning algorithms and molecular fingerprints-Reference-Cited by-同舟云学术

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Effective data-balancing methods for class-imbalanced genotoxicity datasets using machine learning algorithms and molecular fingerprints

Published:2021-11 Issue: Volume:20 Page:100178
ISSN:2468-1113
Container-title:Computational Toxicology
language:en
Short-container-title:Computational Toxicology

Author:

Bae Su-Yong,Lee Jonga,Jeong Jaeseong,Lim Changwon,Choi Jinhee

Funder

Ministry of Science, ICT and Future Planning

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Computer Science Applications,Toxicology

Reference29 articles.

1. DeepTox: Toxicity prediction using deep learning;Mayr;Front. Environ. Sci.,2016

2. Machine learning based toxicity prediction: From chemical structural description to transcriptome analysis;Wu;Int. J. Mol. Sci.,2018

3. Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids;Cao;J. Hazard. Mater.,2018

4. New in silico models to predict in vitro micronucleus induction as marker of genotoxicity;Baderna;J. Hazard. Mater.,2020

5. In silico prediction of chemical genotoxicity using machine learning methods and structural alerts;Fan;Toxicol. Res. Camb.,2018

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