EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search

Abstract Background Elementary flux mode (EFM) analysis is a well-established, yet computationally challenging approach to characterize metabolic networks. Standard algorithms require huge amounts of memory and lack scalability which limits their application to single servers and consequently limits...

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Autores principales:	Bianca A Buchner, Jürgen Zanghellini
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Elementary modes Cobrapy Metabolic modelling Mplrs Lexicographic reverse search Systems biology Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/47b67a40ce9448bda7e170f3ec5fe306
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id	oai:doaj.org-article:47b67a40ce9448bda7e170f3ec5fe306
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spelling	oai:doaj.org-article:47b67a40ce9448bda7e170f3ec5fe3062021-11-14T12:13:10ZEFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search10.1186/s12859-021-04417-91471-2105https://doaj.org/article/47b67a40ce9448bda7e170f3ec5fe3062021-11-01T00:00:00Zhttps://doi.org/10.1186/s12859-021-04417-9https://doaj.org/toc/1471-2105Abstract Background Elementary flux mode (EFM) analysis is a well-established, yet computationally challenging approach to characterize metabolic networks. Standard algorithms require huge amounts of memory and lack scalability which limits their application to single servers and consequently limits a comprehensive analysis to medium-scale networks. Recently, Avis et al. developed mplrs—a parallel version of the lexicographic reverse search (lrs) algorithm, which, in principle, enables an EFM analysis on high-performance computing environments (Avis and Jordan. mplrs: a scalable parallel vertex/facet enumeration code. arXiv:1511.06487 , 2017). Here we test its applicability for EFM enumeration. Results We developed EFMlrs, a Python package that gives users access to the enumeration capabilities of mplrs. EFMlrs uses COBRApy to process metabolic models from sbml files, performs loss-free compressions of the stoichiometric matrix, and generates suitable inputs for mplrs as well as efmtool, providing support not only for our proposed new method for EFM enumeration but also for already established tools. By leveraging COBRApy, EFMlrs also allows the application of additional reaction boundaries and seamlessly integrates into existing workflows. Conclusion We show that due to mplrs’s properties, the algorithm is perfectly suited for high-performance computing (HPC) and thus offers new possibilities for the unbiased analysis of substantially larger metabolic models via EFM analyses. EFMlrs is an open-source program that comes together with a designated workflow and can be easily installed via pip.Bianca A BuchnerJürgen ZanghelliniBMCarticleElementary modesCobrapyMetabolic modellingMplrsLexicographic reverse searchSystems biologyComputer applications to medicine. Medical informaticsR858-859.7Biology (General)QH301-705.5ENBMC Bioinformatics, Vol 22, Iss 1, Pp 1-21 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Elementary modes Cobrapy Metabolic modelling Mplrs Lexicographic reverse search Systems biology Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
spellingShingle	Elementary modes Cobrapy Metabolic modelling Mplrs Lexicographic reverse search Systems biology Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5 Bianca A Buchner Jürgen Zanghellini EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search
description	Abstract Background Elementary flux mode (EFM) analysis is a well-established, yet computationally challenging approach to characterize metabolic networks. Standard algorithms require huge amounts of memory and lack scalability which limits their application to single servers and consequently limits a comprehensive analysis to medium-scale networks. Recently, Avis et al. developed mplrs—a parallel version of the lexicographic reverse search (lrs) algorithm, which, in principle, enables an EFM analysis on high-performance computing environments (Avis and Jordan. mplrs: a scalable parallel vertex/facet enumeration code. arXiv:1511.06487 , 2017). Here we test its applicability for EFM enumeration. Results We developed EFMlrs, a Python package that gives users access to the enumeration capabilities of mplrs. EFMlrs uses COBRApy to process metabolic models from sbml files, performs loss-free compressions of the stoichiometric matrix, and generates suitable inputs for mplrs as well as efmtool, providing support not only for our proposed new method for EFM enumeration but also for already established tools. By leveraging COBRApy, EFMlrs also allows the application of additional reaction boundaries and seamlessly integrates into existing workflows. Conclusion We show that due to mplrs’s properties, the algorithm is perfectly suited for high-performance computing (HPC) and thus offers new possibilities for the unbiased analysis of substantially larger metabolic models via EFM analyses. EFMlrs is an open-source program that comes together with a designated workflow and can be easily installed via pip.
format	article
author	Bianca A Buchner Jürgen Zanghellini
author_facet	Bianca A Buchner Jürgen Zanghellini
author_sort	Bianca A Buchner
title	EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search
title_short	EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search
title_full	EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search
title_fullStr	EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search
title_full_unstemmed	EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search
title_sort	efmlrs: a python package for elementary flux mode enumeration via lexicographic reverse search
publisher	BMC
publishDate	2021
url	https://doaj.org/article/47b67a40ce9448bda7e170f3ec5fe306
work_keys_str_mv	AT biancaabuchner efmlrsapythonpackageforelementaryfluxmodeenumerationvialexicographicreversesearch AT jurgenzanghellini efmlrsapythonpackageforelementaryfluxmodeenumerationvialexicographicreversesearch
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EFMlrs: a Python package for elementary flux mode enumeration via lexicographic reverse search

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