A versatile active learning workflow for optimization of genetic and metabolic networks

Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, we describe METIS, a versatile active machine learning workflow with a simple online interface for the data-driven optimization of biological targets with minimal exp...

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Detalles Bibliográficos
Autores principales: Pandi, Amir, Diehl, Christoph, Yazdizadeh Kharrazi, Ali, Scholz, Scott A., Bobkova, Elizaveta, Faure, Léon, Nattermann, Maren, Adam, David, Chapin, Nils, Foroughijabbari, Yeganeh, Moritz, Charles, Paczia, Nicole, Cortina, Niña Socorro, Faulon, Jean-Loup, Erb, Tobias J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9256728/
https://www.ncbi.nlm.nih.gov/pubmed/35790733
http://dx.doi.org/10.1038/s41467-022-31245-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9256728/
https://www.ncbi.nlm.nih.gov/pubmed/35790733
http://dx.doi.org/10.1038/s41467-022-31245-z

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