Abstract
Motivation: It is known that steady-state flux distributions in metabolic networks can be expressed as non-negative combinations of elementary modes. However, little understanding has been achieved so far in how individual elementary modes contribute to the reconstruction of actual physiological flux distributions. Results: We introduce an approach for decomposing steady-state flux distributions onto elementary modes based on quadratic programming. The decomposition is performed so as to favour modes that are closest to the actual state of the system, i.e. most relevant for biological interpretation. As an illustration, an application of this approach to a model of yeast glycolysis is presented. © The Author 2005. Published by Oxford University Press. All rights reserved.
Original language | English |
---|---|
Pages (from-to) | 204-205 |
Number of pages | 1 |
Journal | Bioinformatics |
Volume | 21 |
Issue number | 2 |
DOIs | |
Publication status | Published - Sep 2005 |