Rxivist logo

MCS^2: Minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

By Reza Miraskarshahi, Hooman Zabeti, Tamon Stephen, Leonid Chindelevitch

Posted 18 Nov 2018
bioRxiv DOI: 10.1101/471250 (published DOI: 10.1093/bioinformatics/btz393)

Motivation: Constraint-based modeling of metabolic networks helps researchers gain insight into the metabolic processes of many organisms, both prokaryotic and eukaryotic. Minimal Cut Sets (MCSs) are minimal sets of reactions whose inhibition blocks a target reaction in a metabolic network. Most approaches for finding the MCSs in constrained-based models require, either as an intermediate step or as a byproduct of the calculation, the computation of the set of elementary flux modes (EFMs), a convex basis for the valid flux vectors in the network. Recently, Ballerstein et al. proposed a method for computing the MCSs of a network without first computing its EFMs, by creating a dual network whose EFMs are a superset of the MCSs of the original network. However, their dual network is always larger than the original network and depends on the target reaction. Here we propose the construction of a different dual network, which is typically smaller than the original network and is independent of the target reaction, for the same purpose. We prove the correctness of our approach, MCS2, and describe how it can be modified to compute the few smallest MCSs for a given target reaction. Results: We compare MCS2 to the method of Ballerstein et al. and two other existing methods. We show that MCS2 succeeds in calculating the full set of MCSs in many models where other approaches cannot finish within a reasonable amount of time. Thus, in addition to its theoretical novelty, our approach provides a practical advantage over existing methods.

Download data

  • Downloaded 384 times
  • Download rankings, all-time:
    • Site-wide: 79,994
    • In bioinformatics: 7,344
  • Year to date:
    • Site-wide: 142,254
  • Since beginning of last month:
    • Site-wide: 84,879

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide