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Model selection in systems and synthetic biology

Kirk, P., Thorne, T. and Stumpf, M. P. H. (2013) Model selection in systems and synthetic biology. Current Opinion in Biotechnology, 24 (4). pp. 767-774. ISSN 0958-1669

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To link to this item DOI: 10.1016/j.copbio.2013.03.012


Developing mechanistic models has become an integral aspect of systems biology, as has the need to differentiate between alternative models. Parameterizing mathematical models has been widely perceived as a formidable challenge, which has spurred the development of statistical and optimisation routines for parameter inference. But now focus is increasingly shifting to problems that require us to choose from among a set of different models to determine which one offers the best description of a given biological system. We will here provide an overview of recent developments in the area of model selection. We will focus on approaches that are both practical as well as build on solid statistical principles and outline the conceptual foundations and the scope for application of such methods in systems biology.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:73509

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