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Maximum entropy decomposition of flux distribution at steady state to elementary modes

Paper ID Volume ID Publish Year Pages File Format Full-Text
21961 43245 2009 6 PDF Available
Title
Maximum entropy decomposition of flux distribution at steady state to elementary modes
Abstract

Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Coefficient (EMC) in cases where no objective biological function is available. Therefore, we proposed a new algorithm implementing the maximum entropy principle (MEP) as an objective function for estimating the EMC. To demonstrate the feasibility of using the MEP in this way, we compared it with Linear Programming and Quadratic Programming for modeling the metabolic networks of Chinese Hamster Ovary, Escherichia coli, and Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants.

Keywords
Maximum entropy principle; Metabolic flux analysis; Enzyme control flux; Elementary mode; Linear programming; Quadratic programming
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Maximum entropy decomposition of flux distribution at steady state to elementary modes
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Publisher
Database: Elsevier - ScienceDirect
Journal: Journal of Bioscience and Bioengineering - Volume 107, Issue 1, January 2009, Pages 84–89
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us