A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Metabolic Adaptation in Cyanobacteria

Machine learning has recently emerged as a promising tool for inferring multi-omic relationships in biological systems. At the same time, genome-scale metabolic models (GSMMs) can be integrated with such multi-omic data to refine phenotypic predictions. In this work, we use a multi-omic machine lear...

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Detalles Bibliográficos
Autores principales: Vijayakumar, Supreeta, Rahman, Pattanathu K.S.M., Angione, Claudio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744713/
https://www.ncbi.nlm.nih.gov/pubmed/33354660
http://dx.doi.org/10.1016/j.isci.2020.101818

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744713/
https://www.ncbi.nlm.nih.gov/pubmed/33354660
http://dx.doi.org/10.1016/j.isci.2020.101818

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