Validation and discovery from computational biology models

Authored by Mike Holcombe, Simon Coakley, Mariam Kiran, Neil Walkinshaw, Phil McMinn

DOI: 10.1016/j.biosystems.2008.03.010

Sponsors: European Union United Kingdom Engineering and Physical Sciences Research Council (EPSRC)

Platforms: FLAME

Model Documentation: Other Narrative

Model Code URLs: Model code not found

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 epithetial tissue. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Tags

Agent-based modelling Simulation Parallel computation X-machines validation and testing