Comparison and improvement of algorithms for computing minimal cut sets

Background 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 prop...

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Vydáno v:BMC bioinformatics Ročník 14; číslo 1; s. 318
Hlavní autoři: Jungreuthmayer, Christian, Nair, Govind, Klamt, Steffen, Zanghellini, Jürgen
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 06.11.2013
BioMed Central Ltd
Témata:
Algorithms
Analysis
Bioinformatics
Biomedical and Life Sciences
Cell metabolism
Comparative analysis
Computational Biology - methods
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer Simulation
Escherichia coli - genetics
Gene Deletion
Gene Knockout Techniques
Humans
Image Processing, Computer-Assisted
Life Sciences
Metabolic Networks and Pathways - genetics
Methodology
Methodology Article
Microarrays
Models, Genetic
Networks analysis
Software
Thermodynamics
Integer programming
Metabolic network analysis
Knockout strategies
Minimal cut sets
Berge’s algorithm
Elementary modes
ISSN:1471-2105, 1471-2105
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Shrnutí:Background 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. However, in their original formulation both algorithms are not fully comparable. Results Here 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. Conclusions Generally, both of our new implementations are by at least one order of magnitude faster than other currently available implementations.
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ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-14-318