Exploring Dimensionality Reduction Techniques for Deep Learning Driven QSAR Models of Mutagenicity

Dimensionality reduction techniques are crucial for enabling deep learning driven quantitative structure-activity relationship (QSAR) models to navigate higher dimensional toxicological spaces, however the use of specific techniques is often arbitrary and poorly explored. Six dimensionality techniqu...

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Detalles Bibliográficos
Autores principales: Kalian, Alexander D., Benfenati, Emilio, Osborne, Olivia J., Gott, David, Potter, Claire, Dorne, Jean-Lou C. M., Guo, Miao, Hogstrand, Christer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10384850/
https://www.ncbi.nlm.nih.gov/pubmed/37505541
http://dx.doi.org/10.3390/toxics11070572

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10384850/
https://www.ncbi.nlm.nih.gov/pubmed/37505541
http://dx.doi.org/10.3390/toxics11070572

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