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Control Theory and Systems Biology$
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Pablo A. Iglesias and Brian P. Ingalls

Print publication date: 2009

Print ISBN-13: 9780262013345

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262013345.001.0001

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PRINTED FROM MIT PRESS SCHOLARSHIP ONLINE (www.mitpress.universitypressscholarship.com). (c) Copyright The MIT Press, 2022. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use.date: 02 July 2022

A Theory of Approximation for Stochastic Biochemical Processes

A Theory of Approximation for Stochastic Biochemical Processes

(p.243) 12 A Theory of Approximation for Stochastic Biochemical Processes
Control Theory and Systems Biology

David Thorsley

Eric Klavins

The MIT Press

This chapter analyzes stochastic models, demonstrating a powerful technique for model comparison and model calibration. The method uses the mathematical construct known as the Wasserstein pseudometric and is general enough to address many modeling problems of interest, such as model comparison, parameter estimation, and model invalidation. This chapter concentrates on stochastic reaction networks. It shows that the Wasserstein pseudometric method proposed has been developed with an eye toward maximum generality. In principle, it can be employed with any class of stochastic model given enough time and enough sample data.

Keywords:   stochastic models, model comparison, model calibration, Wasserstein pseudometric method, parameter estimation, model invalidation, stochastic reaction networks

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