TreeEFM: Calculating Elementary Flux Modes using linear optimization in a tree-based algorithm (with J. Pey, J.A. Villar, L. Tobalina, A. Rezola, J.M. Garcia and F.J. Planes), Bioinformatics, vol.31, 2015, pp897-904.
Motivation: Elementary Flux Modes (EFMs) analysis constitutes a fundamental tool in systems biology. However, the efficient calculation of EFMs in genome-scale metabolic networks (GSMNs) is still a challenge. We present a novel algorithm that uses a Linear Programming-based tree search and efficiently enumerates a subset of EFMs in GSMNs.
Results: Our approach is compared with the EFMEvolver approach, demonstrating a significant improvement in computation time. We also validate the usefulness of our new approach by studying the acetate overflow metabolism in the Escherichia Coli bacteria. To do so, we computed one million EFMs for each energetic amino acid and then analyzed the relevance of each energetic amino acid based on gene/protein expression data and the obtained EFMs. We found good agreement between previous experiments and the conclusions reached using EFMs. Finally, we also analyzed the performance of our approach when applied to large GSMNs.
Availability: The stand-alone software TreeEFM is implemented in C++ and interacts with the open-source linear solver CLP. Contact: email@example.com
Note: The software for calculating Elementary Flux Modes described in this paper is included in the Supplementary Data file associated with the paper
Full paper and Supplementary Data file from journal website
J E Beasley