Abstract
BackgroundConstrained minimal cut sets (cMCSs) have recently been introduced as a framework to enumerate minimal genetic intervention strategies for targeted optimization of metabolic networks. Two different algorithmic schemes (adapted Berge algorithm and binary integer programming) have been proposed to compute cMCSs from elementary modes. However, in their original formulation both algorithms are not fully comparable.ResultsHere we show that by a small extension to the integer program both methods become equivalent. Furthermore, based on well-known preprocessing procedures for integer programming we present efficient preprocessing steps which can be used for both algorithms. We then benchmark the numerical performance of the algorithms in several realistic medium-scale metabolic models. The benchmark calculations reveal (i) that these preprocessing steps can lead to an enormous speed-up under both algorithms, and (ii) that the adapted Berge algorithm outperforms the binary integer approach.ConclusionsGenerally, both of our new implementations are by at least one order of magnitude faster than other currently available implementations.
Highlights
Constrained minimal cut sets have recently been introduced as a framework to enumerate minimal genetic intervention strategies for targeted optimization of metabolic networks
We are concerned with two algorithms [10,11], which are based on elementary mode (EM) analysis [12,13] and
At n = 2 we found 81,168 and 441,095 Minimal cut set (MCS) in E2 and E1, respectively. (The number of MCSs as function of n may be found in Additional file 2: Figure S1.) In all tested situations the adapted Berge algorithm clearly outperforms the binary integer program (BIP)
Summary
Constrained minimal cut sets (cMCSs) have recently been introduced as a framework to enumerate minimal genetic intervention strategies for targeted optimization of metabolic networks. Two different algorithmic schemes (adapted Berge algorithm and binary integer programming) have been proposed to compute cMCSs from elementary modes. In their original formulation both algorithms are not fully comparable. The identification of engineering targets is not straight-forward as cellular metabolism is a highly interconnected and regulated system of reactions. The task is to find a minimal intervention strategy, which removes all unwanted functionality from the network while, at the same time, keeps desirable network properties
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