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pyTFA specifications


Unique identifier OMICS_30651
Name pyTFA
Alternative names matTFA, TMFA
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages MATLAB, Python, Shell (Bash)
License Apache License version 2.0, GNU General Public License version 3.0
Computer skills Advanced
Version 0.7.1-b2
Stability Stable
Maintained Yes




No version available



  • person_outline Vassily Hatzimanikatis

Additional information

The Matlab implementation is available at

Publications for pyTFA

pyTFA citations


In Silico Knockout Screening of Plasmodium falciparum Reactions and Prediction of Novel Essential Reactions by Analysing the Metabolic Network

Biomed Res Int
PMCID: 5896307
DOI: 10.1155/2018/8985718

[…] ics-based Flux Analysis (TFA) is a variant of metabolic flux analysis presented with the capacity of producing thermodynamically feasible flux and metabolite movement profiles on a genome scale [, ]. TMFA includes the utilization of an arrangement of straight thermodynamic constraints notwithstanding the mass balance limitations ordinarily utilized as a part of MFA [, ]. TMFA produces flux circula […]


Pathway design using de novo steps through uncharted biochemical spaces

Nat Commun
PMCID: 5766603
PMID: 29330441
DOI: 10.1038/s41467-017-02362-x

[…] wever, after each step, the trade-off between carbon yield, energy (ATP requirements), and thermodynamic feasibility of the main carbon conversion path often remain unexplored. Instead, tools such as TMFA and EFM are used in a posteriori steps to assess energy and carbon efficiency. Computational tools such as optStoic can be used to design mass and energy balanced pathways. However, they are limi […]


Erroneous energy generating cycles in published genome scale metabolic networks: Identification and removal

PLoS Comput Biol
PMCID: 5413070
PMID: 28419089
DOI: 10.1371/journal.pcbi.1005494

[…] suppress EGCs. In principle, EGCs could be excluded from the solution space by systematically assigning sufficiently detailed thermodynamic constraints. Thermodynamics-Based Metabolic Flux Analysis (TMFA) [], for example, searches for a set of feasible metabolite concentrations such that all reactions proceed in the direction of negative free energy change (ΔG<0) or, equivalently, a ratio of prod […]


Bioenergetics based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks

PLoS Comput Biol
PMCID: 5363809
PMID: 28333921
DOI: 10.1371/journal.pcbi.1005397

[…] nts following the systematic approach defined within the framework of Thermodynamics-based Flux Analysis (TFA) [, , ], which has been also referred to as Thermodynamics-based metabolic Flux Analysis (TMFA) [] and Thermodynamics-based Flux Balance Analysis (TFBA) [, ]. Thermodynamic constraints determine the feasible range of ΔrG’ and hence reduce the uncertainty in the reaction directionalities an […]


Thermodynamics and H2 Transfer in a Methanogenic, Syntrophic Community

PLoS Comput Biol
PMCID: 4509577
PMID: 26147299
DOI: 10.1371/journal.pcbi.1004364

[…] ship between thermodynamics and metabolism, by ensuring that network predictions are consistent with thermodynamic principles [–]. In this study, we used thermodynamics-based metabolic flux analysis (TMFA) to develop a thermodynamic, coculture model of the syntrophic association between the anaerobic bacterium Syntrophobacter fumaroxidans and the methanogenic archaeon Methanospirillum hungatei. In […]


Mechanistic analysis of multi omics datasets to generate kinetic parameters for constraint based metabolic models

BMC Bioinformatics
PMCID: 3571921
PMID: 23360254
DOI: 10.1186/1471-2105-14-32

[…] mes are known to be unexpressed in certain conditions. Thermodynamic constraints have also been imposed to limit the direction a given reaction can proceed, and thermodynamic metabolic flux analysis (TMFA) uses these constraints to ensure that reactions only proceed in the thermodynamically-favorable direction [-]. TMFA models were some of the first constraint-based models that directly accounted […]


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pyTFA institution(s)
Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CentraleSupélec, Université Paris-Saclay, France
pyTFA funding source(s)
Supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 722287, RobustYeast within ERA net project via, and the European Union’s Horizon 2020 research and innovation programme under grant agreement No 686070.

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