Stronger computational modelling of signalling pathways using both continuous and discrete-state methods

Calder, M., Duguid, A., Gilmore, S. and Hillston, J. (2006) Stronger computational modelling of signalling pathways using both continuous and discrete-state methods. Lecture Notes in Computer Science, 3746, pp. 63-77. (doi: 10.1007/11885191_5)

Abstract

Starting from a biochemical signalling pathway model expressed in a process algebra enriched with quantitative information we automatically derive both continuous-space and discrete-state representations suitable for numerical evaluation. We compare results obtained using implicit numerical differentiation formulae to those obtained using approximate stochastic simulation thereby exposing a flaw in the use of the differentiation procedure producing misleading results.

• Item Type: Articles
• Keywords: stochastic process algebra, ordinary differential equations, stochastic simulation
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Calder, Professor Muffy
• Authors: Calder, M., Duguid, A., Gilmore, S., and Hillston, J.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science; Q Science > QA Mathematics
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Lecture Notes in Computer Science
• Publisher: Springer Verlag
• ISSN: 0302-9743
• Copyright Holders: Copyright © 2006 Springer
• First Published: First published in Lecture Notes in Computer Science 3746:63-78
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher