Enhanced flux balance analysis to model metabolic networks

  • Authors:

  • Nishanth Ulhas Nair;Navin Goyal;Nagasuma R. Chandra

  • Affiliations:

  • Laboratory for Computational, Biology and Bioinformatics, EPFL, Switzerland;Microsoft Research India, Bangalore, India;Bioinformatics Centre, Indian Institute of Science, Bangalore, India

  • Venue:
  • Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
  • Year:
  • 2010

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Abstract

Flux Balance Analysis (FBA) is a widely used technique to predict rates of reactions in metabolic networks in cells under steady state using only stoichiometric information about the reactions. In this work, we introduce Enhanced Flux Balance Analysis (eFBA) which is an enhancement of FBA with several advantages over FBA: (1) eFBA seamlessly handles multi-enzyme multi-reaction associations; (2) it estimates (relative) enzyme concentrations optimizing a global objective function; (3) it provides tighter upper and lower bounds on reaction rates; (4) it gives a simpler and more accurate approach to do gene deletion/inhibition studies for finding essential genes; (5) it finds flux-limiting genes/ enzymes. Moreover, eFBA retains the simplicity of FBA, and it models metabolic networks more faithfully.