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

Michael Mundy, Helena Mendes-Soares, Nicholas Chia

Research output: Contribution to journalArticle

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)2416-2418
Number of pages3
JournalBioinformatics
Volume33
Issue number15
DOIs
StatePublished - Aug 1 2017

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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