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BioinformaticsBioinformaticsPeer-reviewed journal article

multiTFA: a Python package for multi-variate Thermodynamics-based Flux Analysis

Vishnuvardhan MahamkaliiD, Tim McCubbiniD, Εlad NooriD, Esteban MarcelliniD, Lars Keld NielseniD

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Abstract

SummaryWe achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly reduces the uncertainty of thermodynamic variables. ResultsWe present multiTFA, a Python implementation of our framework. We evaluated our application using the core E. coli model and achieved a median reduction of 6.8 kJ/mol in reaction Gibbs free energy ranges, while three out of 12 reactions in glycolysis changed from reversible to irreversible. Availability and implementationOur framework along with documentation is available on https://github.com/biosustain/multitfa.

Citations
14

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