Predicting metabolic fluxes from omics data via machine learning: Moving from knowledge-driven towards data-driven approaches

The accurate prediction of phenotypes in microorganisms is a main challenge for systems biology. Genome-scale models (GEMs) are a widely used mathematical formalism for predicting metabolic fluxes using constraint-based modeling methods such as flux balance analysis (FBA). However, they require prio...

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Detalles Bibliográficos
Autores principales: Gonçalves, Daniel M., Henriques, Rui, Costa, Rafael S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590844/
https://www.ncbi.nlm.nih.gov/pubmed/37876626
http://dx.doi.org/10.1016/j.csbj.2023.10.002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590844/
https://www.ncbi.nlm.nih.gov/pubmed/37876626
http://dx.doi.org/10.1016/j.csbj.2023.10.002

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