title: tEFMA: computing thermodynamically feasible elementary flux modes in metabolic networks.
abstract: : Elementary flux modes (EFMs) are important structural tools for the analysis of metabolic networks. It is known that many topologically feasible EFMs are biologically irrelevant. Therefore, tools are needed to find the relevant ones. We present thermodynamic tEFM analysis (tEFMA) which uses the cellular metabolome to avoid the enumeration of thermodynamically infeasible EFMs. Specifically, given a metabolic network and a not necessarily complete metabolome, tEFMA efficiently returns the full set of thermodynamically feasible EFMs consistent with the metabolome. Compared with standard approaches, tEFMA strongly reduces the memory consumption and the overall runtime. Thus tEFMA provides a new way to analyze unbiasedly hitherto inaccessible large-scale metabolic networks.
  
  
  METHODS
  https://github.com/mpgerstl/tEFMA CONTACT: : christian.jungreuthmayer@boku.ac.at or juergen.zanghellini@boku.ac.at
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Austrian Centre of Industrial Biotechnology, Vienna, Austria and Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria Austrian Centre of Industrial Biotechnology, Vienna, Austria and Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
authors.forename: Matthias P
authors.initials: MP
authors.lastname: Gerstl
authors.affiliation: Austrian Centre of Industrial Biotechnology, Vienna, Austria and Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria Austrian Centre of Industrial Biotechnology, Vienna, Austria and Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
authors.forename: Christian
authors.initials: C
authors.lastname: Jungreuthmayer
authors.affiliation: Austrian Centre of Industrial Biotechnology, Vienna, Austria and Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria Austrian Centre of Industrial Biotechnology, Vienna, Austria and Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Zanghellini
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D064688:Metabolic Flux Analysis / Q000379:methods*; D053858:Metabolic Networks and Pathways; D012984:Software; D013816:Thermodynamics