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Model selection in systems and synthetic biology

Paper ID Volume ID Publish Year Pages File Format Full-Text
15669 42465 2013 8 PDF Available
Title
Model selection in systems and synthetic biology
Abstract

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.

Graphical abstractFigure optionsDownload full-size imageDownload high-quality image (129 K)Download as PowerPoint slideHighlights•Model selection allows us to compare different mechanistic hypotheses.•Modern approaches balance model power and complexity.•Dynamical systems pose particular challenges to model selection.•Model selection can also inform synthetic biology.

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Model selection in systems and synthetic biology
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Publisher
Database: Elsevier - ScienceDirect
Journal: Current Opinion in Biotechnology - Volume 24, Issue 4, August 2013, Pages 767–774
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