TY - GEN
T1 - Investigating co-infection dynamics through evolution of bio-PEPA model parameters
T2 - 10th International Conference on Computational Methods in Systems Biology, CMSB 2012
AU - Marco, David
AU - Scott, Erin
AU - Cairns, David
AU - Graham, Andrea
AU - Allen, Judi
AU - Mahajan, Simmi
AU - Shankland, Carron
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84867883579&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867883579&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33636-2_14
DO - 10.1007/978-3-642-33636-2_14
M3 - Conference contribution
AN - SCOPUS:84867883579
SN - 9783642336355
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 227
EP - 246
BT - Computational Methods in Systems Biology - 10th International Conference, CMSB 2012, Proceedings
Y2 - 3 October 2012 through 5 October 2012
ER -