A hybrid approach to piecewise modelling of biochemical systems

Authors:
Zujian Wu;Shengxiang Yang;David Gilbert
Affiliations:
School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex, UK;School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex, UK;School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex, UK
Venue:
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Year:
2012

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Abstract

Modelling biochemical systems has received considerable attention over the last decade from scientists and engineers across a number of fields, including biochemistry, computer science, and mathematics. Due to the complexity of biochemical systems, it is natural to construct models of the biochemical systems incrementally in a piecewise manner. This paper proposes a hybrid approach which applies an evolutionary algorithm to select and compose pre-defined building blocks from a library of atomic models, mutating their products, thus generating complex systems in terms of topology, and employs a global optimization algorithm to fit the kinetic rates. Experiments using two signalling pathways show that given target behaviours it is feasible to explore the model space by this hybrid approach, generating a set of synthetic models with alternative structures and similar behaviours to the desired ones.