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Researchers at Montana State University Report New Data on Bioinformatics (Complete enumeration of elementary flux modes through scalable...

July 8, 2014

Researchers at Montana State University Report New Data on Bioinformatics (Complete enumeration of elementary flux modes through scalable demand-based subnetwork definition)

By a News Reporter-Staff News Editor at Information Technology Newsweekly -- New research on Bioinformatics is the subject of a report. According to news reporting from Bozeman, Montana, by VerticalNews journalists, research stated, "Elementary flux mode analysis (EFMA) decomposes complex metabolic network models into tractable biochemical pathways, which have been used for rational design and analysis of metabolic and regulatory networks. However, application of EFMA has often been limited to targeted or simplified metabolic network representations due to computational demands of the method."

The news correspondents obtained a quote from the research from Montana State University, "Division of biological networks into subnetworks enables the complete enumeration of elementary flux modes (EFMs) for metabolic models of a broad range of complexities, including genome-scale. Here, subnetworks are defined using serial dichotomous suppression and enforcement of flux through model reactions. Rules for selecting appropriate reactions to generate subnetworks are proposed and tested; three test cases, including both prokaryotic and eukaryotic network models, verify the efficacy of these rules and demonstrate completeness and reproducibility of EFM enumeration. Division of models into subnetworks is demand-based and automated; computationally intractable subnetworks are further divided until the entire solution space is enumerated. To demonstrate the strategy's scalability, the splitting algorithm was implemented using an EFMA software package (EFMTool) and Windows PowerShell on a 50 node Microsoft high performance computing cluster. Enumeration of the EFMs in a genomescale metabolic model of a diatom, Phaeodactylum tricornutum, identified similar to 2 billion EFMs."

According to the news reporters, the research concluded: "The output represents an order of magnitude increase in EFMs computed compared with other published algorithms and demonstrates a scalable framework for EFMA of most systems."

For more information on this research see: Complete enumeration of elementary flux modes through scalable demand-based subnetwork definition. Bioinformatics, 2014;30(11):1569-1578. Bioinformatics can be contacted at: Oxford Univ Press, Great Clarendon St, Oxford OX2 6DP, England. (Oxford University Press -; Bioinformatics -

Our news journalists report that additional information may be obtained by contacting K.A. Hunt, Montana State University, Dept. of Chem & Biol Engn, Bozeman, MT 59717, United States. Additional authors for this research include J.P. Folsom, R.L. Taffs and R.P. Carlson.

Keywords for this news article include: Bozeman, Montana, United States, Bioinformatics, North and Central America

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Source: Information Technology Newsweekly

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