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BMCBI
2008

Predicting biological system objectives de novo from internal state measurements

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Predicting biological system objectives de novo from internal state measurements
Background: Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For example, methods are emerging to engineer cells to optimally produce byproducts of commercial value, such as bioethanol, as well as molecular compounds for disease therapy. Flux balance analysis (FBA) is an optimization framework that aids in this interrogation by generating predictions of optimal flux distributions in cellular networks. Critical features of FBA are the definition of a biologically relevant objective function (e.g., maximizing the rate of synthesis of biomass, a unit of measurement of cellular growth) and the subsequent application of linear programming (LP) to identify fluxes through a reaction network. Despite the success of FBA, a central remaining challenge is the definition of a network objective with biological meaning. Results: We present a novel method called Biological Objective Solution ...
Erwin P. Gianchandani, Matthew A. Oberhardt, Antho
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Erwin P. Gianchandani, Matthew A. Oberhardt, Anthony P. Burgard, Costas D. Maranas, Jason A. Papin
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