Details

Autor(en) / Beteiligte

• Vlassis, Nikos
• Pacheco, Maria Pires
• Sauter, Thomas
• Ouzounis, Christos A.

Titel

Fast reconstruction of compact context-specific metabolic network models

Ist Teil von

• PLoS computational biology, 2014-01, Vol.10 (1), p.e1003424-e1003424

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2014

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• 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.