Developing a GNN-based AI model to predict mitochondrial toxicity using the bagging method
Author:
Affiliation:
1. Toxicogenomics Informatics Project, National Institutes of Biomedical Innovation, Health and Nutrition
2. Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University
Publisher
Japanese Society of Toxicology
Link
https://www.jstage.jst.go.jp/article/jts/49/3/49_117/_pdf
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2. Bento, A.P., Hersey, A., Félix, E., Landrum, G., Gaulton, A., Atkinson, F., Bellis, L.J., De Veij, M. and Leach, A.R. (2020): An open source chemical structure curation pipeline using RDKit. J. Cheminform., 12, 51.
3. Breiman, L. (1996): Bagging predictors. Mach. Learn., 24, 123-140.
4. Bringezu, F., Gómez-Tamayo, J.C. and Pastor, M. (2021): Ensemble prediction of mitochondrial toxicity using machine learning technology. Comput. Toxicol., 20, 100189.
5. Brody, S., Alon, U. and Yahav, E. (2021): How attentive are graph attention networks? arXiv preprint arXiv:2105.14491.
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