Mackinac: a bridge between ModelSEED and COBRApy to generate and analyze genome-scale metabolic models

SUMMARY: Reconstructing and analyzing a large number of genome-scale metabolic models is a fundamental part of the integrated study of microbial communities; however, two of the most widely used frameworks for building and analyzing models use different metabolic network representations. Here we des...

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Detalles Bibliográficos
Autores principales: Mundy, Michael, Mendes-Soares, Helena, Chia, Nicholas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860119/
https://www.ncbi.nlm.nih.gov/pubmed/28379466
http://dx.doi.org/10.1093/bioinformatics/btx185
Descripción
Sumario:SUMMARY: Reconstructing and analyzing a large number of genome-scale metabolic models is a fundamental part of the integrated study of microbial communities; however, two of the most widely used frameworks for building and analyzing models use different metabolic network representations. Here we describe Mackinac, a Python package that combines ModelSEED’s ability to automatically reconstruct metabolic models with COBRApy’s advanced analysis capabilities to bridge the differences between the two frameworks and facilitate the study of the metabolic potential of microorganisms. AVAILABILITY AND IMPLEMENTATION: This package works with Python 2.7, 3.4, and 3.5 on MacOS, Linux and Windows. The source code is available from https://github.com/mmundy42/mackinac.

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