Investigating co-infection dynamics through evolution of bio-PEPA model parameters: A combined process algebra and evolutionary computing approach

David Marco, Erin Scott, David Cairns, Andrea Graham, Judi Allen, Simmi Mahajan, Carron Shankland

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Process algebras are an effective method for defining models of complex interacting biological processes, but defining a model requires expertise from both modeller and domain expert. In addition, even with the right model, tuning parameters to allow model outputs to match experimental data can be difficult. This is the well-known parameter fitting problem. Evolutionary algorithms provide effective methods for finding solutions to optimisation problems with large search spaces and are well suited to investigating parameter fitting problems. We present the Evolving Process Algebra (EPA) framework which combines an evolutionary computation approach with process algebra modelling to produce parameter distribution data that provides insight into the parameter space of the biological system under investigation. The EPA framework is demonstrated through application to a novel example: T helper cell activation in the immune system in the presence of co-infection.

Original languageEnglish (US)
Title of host publicationComputational Methods in Systems Biology - 10th International Conference, CMSB 2012, Proceedings
Pages227-246
Number of pages20
DOIs
StatePublished - Oct 30 2012
Event10th International Conference on Computational Methods in Systems Biology, CMSB 2012 - London, United Kingdom
Duration: Oct 3 2012Oct 5 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7605 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Conference on Computational Methods in Systems Biology, CMSB 2012
CountryUnited Kingdom
CityLondon
Period10/3/1210/5/12

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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