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Fast reconstruction of compact context-specific metabolic network models
Vlassis, Nikos; Pacheco, Maria; Sauter, Thomas
2013
 

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Abstract :
[en] Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can routinely involve large numbers of tests under different conditions and extensive parameter tuning, which calls for fast algorithms. We present FASTCORE, a generic algorithm for reconstructing context-specific metabolic network models from global genome-wide metabolic network models such as Recon X. FASTCORE takes as input a core set of reactions that are known to be active in the context of interest (e.g., cell or tissue), and it searches for a flux consistent subnetwork of the global network that contains all reactions from the core set and a minimal set of additional reactions. Our key observation is that a minimal consistent reconstruction can be defined via a set of sparse modes of the global network, and FASTCORE iteratively computes such a set via a series of linear programs. Experiments on liver data demonstrate speedups of several orders of magnitude, and significantly more compact reconstructions, over a chief rival method. Given its simplicity and its excellent performance, FASTCORE can form the backbone of many future metabolic network reconstruction algorithms.
Disciplines :
Computer science
Biochemistry, biophysics & molecular biology
Author, co-author :
Vlassis, Nikos ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Pacheco, Maria ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Sauter, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Language :
English
Title :
Fast reconstruction of compact context-specific metabolic network models
Publication date :
2013
Available on ORBilu :
since 17 November 2013

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