Format

Send to

Choose Destination
PLoS Comput Biol. 2014 Jan;10(1):e1003424. doi: 10.1371/journal.pcbi.1003424. Epub 2014 Jan 16.

Fast reconstruction of compact context-specific metabolic network models.

Author information

1
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg City, Luxembourg.
2
Life Sciences Research Unit, University of Luxembourg, Luxembourg City, Luxembourg.

Abstract

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 rival method. Given its simplicity and its excellent performance, fastcore can form the backbone of many future metabolic network reconstruction algorithms.

PMID:
24453953
PMCID:
PMC3894152
DOI:
10.1371/journal.pcbi.1003424
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Public Library of Science Icon for PubMed Central
Loading ...
Support Center