Jan Bert van Klinken1, Ko Willems van Dijk2. 1. Department of Human Genetics Einthoven Laboratory for Experimental Vascular Medicine. 2. Department of Human Genetics Einthoven Laboratory for Experimental Vascular Medicine Department of Medicine, Division of Endocrinology, LUMC, Leiden, The Netherlands.
Abstract
UNLABELLED: Elementary flux mode (EFM) analysis is a powerful technique for determining the metabolic capacities and robustness of stoichiometric networks. Recently, several improvements have been made to the algorithm for enumerating the EFMs, making the study of large models possible. However, currently these tools require high performance workstations to perform large-scale EFM computations, thus limiting their applicability. We developed a more time and memory efficient implementation of the algorithm for EFM enumeration in MATLAB, called FluxModeCalculator, which enables large-scale EFM computation on ordinary desktop computers. AVAILABILITY AND IMPLEMENTATION: FluxModeCalculator is open source and freely available under the terms of the GNU General Public License v3.0 at http://www.lumc.nl/jan-bert-van-klinken CONTACT: j.b.van_klinken@lumc.nl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
UNLABELLED: Elementary flux mode (EFM) analysis is a powerful technique for determining the metabolic capacities and robustness of stoichiometric networks. Recently, several improvements have been made to the algorithm for enumerating the EFMs, making the study of large models possible. However, currently these tools require high performance workstations to perform large-scale EFM computations, thus limiting their applicability. We developed a more time and memory efficient implementation of the algorithm for EFM enumeration in MATLAB, called FluxModeCalculator, which enables large-scale EFM computation on ordinary desktop computers. AVAILABILITY AND IMPLEMENTATION: FluxModeCalculator is open source and freely available under the terms of the GNU General Public License v3.0 at http://www.lumc.nl/jan-bert-van-klinken CONTACT: j.b.van_klinken@lumc.nl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Steffen Klamt; Georg Regensburger; Matthias P Gerstl; Christian Jungreuthmayer; Stefan Schuster; Radhakrishnan Mahadevan; Jürgen Zanghellini; Stefan Müller Journal: PLoS Comput Biol Date: 2017-04-13 Impact factor: 4.475