BOFdat: generating biomass objective function stoichiometric coefficients from experimental data

@article{Lachance2018BOFdatGB,
  title={BOFdat: generating biomass objective function stoichiometric coefficients from experimental data},
  author={Jean-Christophe Lachance and Jonathan M. Monk and C. Lloyd and Yara Seif and B. Palsson and S{\'e}bastien Rodrigue and A. Feist and Zachary A. King and P. Jacques},
  journal={bioRxiv},
  year={2018}
}
Genome-scale models (GEMs) rely on a biomass objective function (BOF) to predict phenotype from genotype. Here we present BOFdat, a Python package that offers functions to generate biomass objective function stoichiometric coefficients (BOFsc) from macromolecular cell composition and relative abundances of macromolecules obtained from omic datasets. Growth-associated and non-growth associated maintenance (GAM and NGAM) costs can also be calculated by BOFdat. BOFdat is freely available on the… Expand
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