DocumentCode :
16439
Title :
Fast Computation of Minimal Cut Sets in Metabolic Networks with a Berge Algorithm that Utilizes Binary Bit Pattern Trees
Author :
Jungreuthmayer, Christian ; Beurton-Aimar, Marie ; Zanghellini, Jurgen
Author_Institution :
Dept. of Biotechnol., Univ. of Natural Resources & Life Sci., Vienna, Austria
Volume :
10
Issue :
5
fYear :
2013
fDate :
Sept.-Oct. 2013
Firstpage :
1
Lastpage :
1
Abstract :
Minimal cut sets are a valuable tool for analyzing metabolic networks and for identifying optimal gene intervention strategies by eliminating unwanted metabolic functions and keeping desired functionality. Minimal cut sets rely on the concept of elementary flux modes which are sets of indivisible metabolic pathways under steady state condition. However, the computation of minimal cut sets is non-trivial, as even medium sized metabolic networks with just 100 reactions easily have several hundred million elementary flux modes. We developed a minimal cut set tool that implements the well known Berge algorithm and utilizes a novel approach to significantly reduce the program run time by using binary bit pattern trees. By using the introduced tree approach the size of metabolic models that can be analyzed and optimized by minimal cut sets is pushed to new and considerably higher limits.
Keywords :
biochemistry; biological techniques; biology computing; decision trees; genetics; Berge algorithm; binary bit pattern trees; desired functionality; elementary flux modes; fast computation; indivisible metabolic pathways; medium sized metabolic network; metabolic network analysis; metabolic size model; minimal cut set computation; minimal cut set tool; optimal gene intervention strategy identification; program run time reduction; steady state condition; unwanted metabolic function elimination; Benchmark testing; Biochemistry; Bioinformatics; Computational biology; Instruction sets; Runtime; Algorithms; Benchmark testing; Biochemistry; Bioinformatics; Biology and genetics; Computational biology; IEEE transactions; Instruction sets; Runtime;
fLanguage :
English
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
1545-5963
Type :
jour
DOI :
10.1109/TCBB.2013.116
Filename :
6604386
Link To Document :
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