Computational inference in systems biology

Macdonald, B. and Husmeier, D. (2015) Computational inference in systems biology. In: Ortuño, F. and Rojas, I. (eds.) Bioinformatics and Biomedical Engineering:Third International Conference, IWBBIO 2015, Granada, Spain, April 15-17, 2015: Proceedings, Part II. Series: Lecture Notes in Computer Science (9044). Springer, pp. 276-288. ISBN 9783319164809 (doi: 10.1007/978-3-319-16480-9_28)

107132.pdf - Accepted Version



Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs), is a challenging problem. The computational costs associated with repeatedly solving the ODEs are often high. 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, and conducts a comparative evaluation with current methods used for parameter inference in ODEs.

Item Type:Book Sections
Glasgow Author(s) Enlighten ID:Husmeier, Professor Dirk and Macdonald, Dr Benn
Authors: Macdonald, B., and Husmeier, D.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Copyright Holders:Copyright © 2015 Springer International Publishing Switzerland
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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