Macdonald, B., Dondelinger, F. and Husmeier, D. (2013) Inference in complex biological systems with Gaussian processes and parallel tempering. In: Muggeo, V.M.R., Capursi, V., Boscaino, G. and Lovison, G. (eds.) Proceedings of the 28th International Workshop on Statistical Modelling. Gruppo Istituto Poligrafico Europeo SRL, pp. 673-676. ISBN 9788896251492
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Abstract
Parameter inference in mathematical models of complex biological systems, expressed as coupled ordinary differential equations (ODEs), is a challenging problem. These depend on kinetic parameters, which cannot all be measured and have to be ascertained a different way. However, the computational costs associated with repeatedly solving the ODEs are often staggering, making many techniques impractical. Therefore, aimed at reducing this cost, new concepts using gradient matching have been proposed. This paper combines current adaptive gradient matching approaches, using Gaussian processes, with a parallel tempering scheme, in order to compare 2 different paradigms using the same nonlinear regression method. We use 2 ODE systems to assess our technique, showing an improvement over the recent method in Calderhead et al. (2008).
Item Type: | Book Sections |
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Status: | Published |
Glasgow Author(s) Enlighten ID: | Husmeier, Professor Dirk and Macdonald, Dr Benn and Dondelinger, Mr Frank |
Authors: | Macdonald, B., Dondelinger, F., and Husmeier, D. |
College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
Publisher: | Gruppo Istituto Poligrafico Europeo SRL |
ISBN: | 9788896251492 |
Copyright Holders: | Copyright © 2013 Statistical Modelling Society |
Publisher Policy: | Reproduced with the permission of the editor |
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