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SRI Speeds Development of Genome-Scale Models of Metabolic Networks
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SRI Speeds Development of Genome-Scale Models of Metabolic Networks

SRI Speeds Development of Genome-Scale Models of Metabolic Networks
News

SRI Speeds Development of Genome-Scale Models of Metabolic Networks

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MetaFlux is a new software tool to substantially decrease the time required for researchers to construct genome-scale models of metabolic networks.

Metabolic networks are the complete set of metabolic and physical processes that determine the physiological and biochemical properties of a cell. Genome-scale models are used to predict cell growth rate, combinations of chemicals that can support cell growth, and which genes will cause cell death if they are inactivated.

It may also yield insights about growth of bacteria that cannot currently be grown in a laboratory.
MetaFlux software couples flux balance analysis (FBA), a mathematical method to analyze metabolism, with pathway databases that contain information about the network of interactions between proteins and small molecules that forms the biochemical factory of a cell.

"Genome-scale models are very time consuming to construct, because they require an exact description of the hundreds of biochemical reactions within a cell—and a single missing reaction can render a model nonfunctional," said Peter D. Karp, Ph.D., director, Bioinformatics Research Group, SRI International. "Our goals were to speed up the development of these models and allow a wider community of scientists to build them. SRI's Bioinformatics Research group has already developed two different FBA models using MetaFlux, each within one month of effort."

Based on mixed integer linear programming, MetaFlux uses a multiple gap-filling method to accelerate the development of FBA models. This method generates the models directly from pathway/genome databases, which can be constructed, queried, and visualized using SRI's Pathway Tools software. MetaFlux can also suggest additional reactions, nutrients, and secreted metabolites to complete a model.

During model development, MetaFlux will identify the subset of biomass metabolites (end products of biosynthesis) that cannot currently be produced. The software also paints reaction flux rates onto an automatically generated organism-specific metabolic map diagram, much like an online road map shows traffic flow rates.

MetaFlux is part of Pathway Tools, available freely to academic users and for a fee to commercial users. An article describing MetaFlux is in the online edition of the journal Bioinformatics at http://oxford.ly/metaflux, and will appear in the journal's 3rd issue of 2012, which publishes in early February.

The project described was supported by award number R01GM080746 from the National Institute of General Medical Sciences. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health.

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