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Package to generate biomass objective functions to update genome-scale metabolic models.

Project description

BioModTool : Biomass Modeling Tool

What is BioModTool ?

BioModTool is a Python library allowing easy generation of biomass objective functions for genome scale metabolic models from user data. BioModTool loads biomass composition data in the form of a structured Excel file previously completed by the user, normalizes, converts these data into model compatible unit (mmol.gDW-1), and creates a structured biomass objective to update a metabolic model. BioModTool can be run as Python command-lines but it also comes with an interface allowing its use by non-modelers.

Installation

Use pip to install BioModTool from PyPI

 pip install BioModTool

In case you downloaded or cloned the source code from GitHub

 pip install <path-to-BioModTool-repo> 

Documentation

Documentation is available on GitHub.

Application examples

BioModTool was applied to GEM of two bacteria species Escherichia coli (iML1515, Monk et al. 2017) and Alicyclobacillus acidocaldarius (CNA_Alicyclo, Beck, Hunt et Carlson 2018), and one microalga Chlamydomonas reinhardtii (iRC1080, Chang et al. 2011). These examples illustrate the three different contexts in which BioModTool can be used:

  • Add a three level BOF in a model in which metabolic formula are available: iML1515
  • Add a two level BOF in a model in which metabolic formula are not available: CNA_Alicyclo
  • Add a one level BOF in a model in which metabolic formula are not available: iRC1080

All scripts and results of these three application examples are fully available on GitHub.

Authors/Contributors

Clémence Dupont-Thibert1,2, Sylvaine Roy1, Gilles Curien1, Maxime Durot2

1 - Université Grenoble Alpes, CNRS, CEA, INRAE, Interdisciplinary Research Institute of Grenoble, IRIG-Laboratoire de Physiologie Cellulaire et Végétale, 17 Avenue des Martyrs, 38000 Grenoble, France
2 - TotalEnergies, OneTech, Centre de Recherche de Solaize CRES, Chemin du Canal, 69360 Solaize, France

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