A Comparison of Nine Machine Learning Mutagenicity Models and Their Application for Predicting Pyrrolizidine Alkaloids

Random forest, support vector machine, logistic regression, neural networks and k-nearest neighbor (lazar) algorithms, were applied to a new Salmonella mutagenicity dataset with 8,290 unique chemical structures utilizing MolPrint2D and Chemistry Development Kit (CDK) descriptors. Crossvalidation acc...

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Detalles Bibliográficos
Autores principales: Helma, Christoph, Schöning, Verena, Drewe, Jürgen, Boss, Philipp
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Pharmacology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339974/
https://www.ncbi.nlm.nih.gov/pubmed/34366864
http://dx.doi.org/10.3389/fphar.2021.708050

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339974/
https://www.ncbi.nlm.nih.gov/pubmed/34366864
http://dx.doi.org/10.3389/fphar.2021.708050

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