Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/13009
Title: Validation and discovery from computational biology models.
Authors: Kiran, M
Coakley, S
Walkinshaw, N
McMinn, P
Holcombe, M
First Published: Jul-2008
Citation: BIOSYSTEMS, 2008, 93 (1-2), pp. 141-150
Abstract: Simulation software is often a fundamental component in systems biology projects and provides a key aspect of the integration of experimental and analytical techniques in the search for greater understanding and prediction of biology at the systems level. It is important that the modelling and analysis software is reliable and that techniques exist for automating the analysis of the vast amounts of data which such simulation environments generate. A rigorous approach to the development of complex modelling software is needed. Such a framework is presented here together with techniques for the automated analysis of such models and a process for the automatic discovery of biological phenomena from large simulation data sets. Illustrations are taken from a major systems biology research project involving the in vitro investigation, modelling and simulation of epithelial tissue.
DOI Link: 10.1016/j.biosystems.2008.03.010
ISSN: 0303-2647
Links: http://hdl.handle.net/2381/13009
Type: Journal Article
Appears in Collections:Published Articles, Dept. of Computer Science

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