Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological systems from sparse experimental data. In the present work, BINNs are trained in a supervised learning framework to approxima...

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Detalles Bibliográficos
Autores principales: Lagergren, John H., Nardini, John T., Baker, Ruth E., Simpson, Matthew J., Flores, Kevin B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732115/
https://www.ncbi.nlm.nih.gov/pubmed/33259472
http://dx.doi.org/10.1371/journal.pcbi.1008462

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732115/
https://www.ncbi.nlm.nih.gov/pubmed/33259472
http://dx.doi.org/10.1371/journal.pcbi.1008462

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