Stronger Computational Modelling of Signalling Pathways Using Both Continuous and Discrete-State Methods | Zendy

Muffy Calder | Zendy; Adam Duguid | Zendy; Stephen Gilmore | Zendy; Jane Hillston | Zendy

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Stronger Computational Modelling of Signalling Pathways Using Both Continuous and Discrete-State Methods

Author(s) -

Muffy Calder,

Adam Duguid,

Stephen Gilmore,

Jane Hillston

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-46166-3

DOI - 10.1007/11885191_5

Subject(s) - signalling , discrete modelling , signalling pathways , state space , state (computer science) , computer science , process (computing) , discrete time and continuous time , automatic differentiation , stochastic process , theoretical computer science , mathematics , algorithm , discrete system , mathematical economics , statistics , biology , signal transduction , programming language , computation , biochemistry

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.

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