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MEWpy: a computational strain optimization workbench in Python

SUMMARY: Metabolic Engineering aims to favour the overproduction of native, as well as non-native, metabolites by modifying or extending the cellular processes of a specific organism. In this context, Computational Strain Optimization (CSO) plays a relevant role by putting forward mathematical appro...

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Detalles Bibliográficos
Autores principales: Pereira, Vítor, Cruz, Fernando, Rocha, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8388025/
https://www.ncbi.nlm.nih.gov/pubmed/33459757
http://dx.doi.org/10.1093/bioinformatics/btab013
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author Pereira, Vítor
Cruz, Fernando
Rocha, Miguel
author_facet Pereira, Vítor
Cruz, Fernando
Rocha, Miguel
author_sort Pereira, Vítor
collection PubMed
description SUMMARY: Metabolic Engineering aims to favour the overproduction of native, as well as non-native, metabolites by modifying or extending the cellular processes of a specific organism. In this context, Computational Strain Optimization (CSO) plays a relevant role by putting forward mathematical approaches able to identify potential metabolic modifications to achieve the defined production goals. We present MEWpy, a Python workbench for metabolic engineering, which covers a wide range of metabolic and regulatory modelling approaches, as well as phenotype simulation and CSO algorithms. AVAILABILITY AND IMPLEMENTATION: MEWpy can be installed from PyPi (pip install mewpy), the source code being available at https://github.com/BioSystemsUM/mewpy under the GPL license.
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spelling pubmed-83880252021-08-26 MEWpy: a computational strain optimization workbench in Python Pereira, Vítor Cruz, Fernando Rocha, Miguel Bioinformatics Applications Notes SUMMARY: Metabolic Engineering aims to favour the overproduction of native, as well as non-native, metabolites by modifying or extending the cellular processes of a specific organism. In this context, Computational Strain Optimization (CSO) plays a relevant role by putting forward mathematical approaches able to identify potential metabolic modifications to achieve the defined production goals. We present MEWpy, a Python workbench for metabolic engineering, which covers a wide range of metabolic and regulatory modelling approaches, as well as phenotype simulation and CSO algorithms. AVAILABILITY AND IMPLEMENTATION: MEWpy can be installed from PyPi (pip install mewpy), the source code being available at https://github.com/BioSystemsUM/mewpy under the GPL license. Oxford University Press 2021-01-18 /pmc/articles/PMC8388025/ /pubmed/33459757 http://dx.doi.org/10.1093/bioinformatics/btab013 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Pereira, Vítor
Cruz, Fernando
Rocha, Miguel
MEWpy: a computational strain optimization workbench in Python
title MEWpy: a computational strain optimization workbench in Python
title_full MEWpy: a computational strain optimization workbench in Python
title_fullStr MEWpy: a computational strain optimization workbench in Python
title_full_unstemmed MEWpy: a computational strain optimization workbench in Python
title_short MEWpy: a computational strain optimization workbench in Python
title_sort mewpy: a computational strain optimization workbench in python
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8388025/
https://www.ncbi.nlm.nih.gov/pubmed/33459757
http://dx.doi.org/10.1093/bioinformatics/btab013
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