Niu, M., Rogers, S. , Filippone, M. and Husmeier, D. (2017) Parameter Inference in Differential Equation Models of Biopathways using Time Warped Gradient Matching. In: 13th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, Stirling, UK, 01-03 Sep 2016, pp. 145-159. ISBN 9783319678337 (doi: 10.1007/978-3-319-67834-4_12)
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Abstract
Parameter inference in mechanistic models of biopathways based on systems of coupled differential equations is a topical yet computationally challenging problem, due to the fact that each parameter adaptation involves a numerical integration of the differential equations. Techniques based on gradient matching, which aim to minimize the discrepancy between the slope of a data interpolant and the derivatives predicted from the differential equations, offer a computationally appealing shortcut to the inference problem. However, gradient matching critically hinges on the smoothing scheme for function interpolation, with spurious wiggles in the interpolant having a dramatic effect on the subsequent inference. The present article demonstrates that a time warping approach aiming to homogenize intrinsic functional length scales can lead to a signifi- cant improvement in parameter estimation accuracy. We demonstrate the effectiveness of this scheme on noisy data from a dynamical system with periodic limit cycle and a biopathway.
Item Type: | Conference Proceedings |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Husmeier, Professor Dirk and Rogers, Dr Simon and Filippone, Dr Maurizio and Niu, Dr Mu |
Authors: | Niu, M., Rogers, S., Filippone, M., and Husmeier, D. |
College/School: | College of Science and Engineering > School of Computing Science College of Science and Engineering > School of Mathematics and Statistics |
ISSN: | 0302-9743 |
ISBN: | 9783319678337 |
Published Online: | 17 October 2017 |
Copyright Holders: | Copyright © 2017 Springer International Publishing AG |
First Published: | First published in Lecture Notes in Computer Science 10477: 145-159 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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