1. Mackinac: a bridge between ModelSEED and COBRApy to generate and analyze genome-scale metabolic models
- Author
-
Nicholas Chia, Helena Mendes-Soares, and Michael B. Mundy
- Subjects
0301 basic medicine ,Statistics and Probability ,Source code ,Computer science ,media_common.quotation_subject ,0206 medical engineering ,Genome scale ,Metabolic network ,02 engineering and technology ,Biochemistry ,Genome ,Models, Biological ,Bridge (nautical) ,03 medical and health sciences ,Software ,Metabolic potential ,Molecular Biology ,media_common ,computer.programming_language ,biology ,Bacteria ,business.industry ,Systems Biology ,Computational Biology ,Python (programming language) ,biology.organism_classification ,Applications Notes ,Computer Science Applications ,Computational Mathematics ,030104 developmental biology ,Computational Theory and Mathematics ,Software engineering ,business ,computer ,020602 bioinformatics ,Metabolic Networks and Pathways - Abstract
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. Contact: mundy.michael@mayo.edu or soares.maria@mayo.edu
- Published
- 2017