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Title:	Model discrimination using data collaboration (Abstract only)
Authors:	Feeley, Ryan Frenklach, Michael Onsum, Matt Russi, Trent Arkin, Adam Packard, Andrew
Issue Date:	7-Mar-2006
Publisher:	American Chemical Society
Citation:	Journal of Physical Chemistry A; vol. 110, no. 21, pp. 6803-6813 (2006)
Type:	journal article
Pages:	11
Abstract:	This paper introduces a practical data-driven method to discriminate among large-scale kinetic reaction models. The approach centers around a computable measure of model/data mismatch. We introduce two provably convergent algorithms that were developed to accommodate large ranges of uncertainty in the model parameters. The algorithms are demonstrated on a simple toy example and a methane combustion model with more than 100 uncertain parameters. They are subsequently used to discriminate between two models for a contemporarily studied biological signaling network.
URI:	http://ds.heavyoil.utah.edu/dspace/handle/123456789/9958
Appears in Collections:	ICSE Digital Library

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