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Compositional Modeling of Biological Systems

Authors: Zamborszky, Judit;

Compositional Modeling of Biological Systems

Abstract

Molecular interactions are wired in a fascinating way resulting in complex behavior of bio-logical systems. Theoretical modeling provides us a useful framework for understanding the dynamics and the function of such networks. The complexity of the biological systems calls for conceptual tools that manage the combinatorial explosion of the set of possible interac-tions. A suitable conceptual tool to attack complexity is compositionality, already success-fully used in the process algebra field to model computer systems. We rely on the BlenX programming language, originated by the beta-binders process calculus, to specify and si-mulate high-level descriptions of biological circuits. Gillespieâ€TMs stochastic simulation algo-rithm applied for BlenX simulations requires the decomposition of phenomenological func-tions into basic elementary reactions. Systematic unpacking of complex reaction mechanisms into BlenX templates is shown. The estimation/derivation of missing parameters and the challenges emerging from compositional model building in stochastic process algebras are discussed. A biological example on circadian clock is presented as a case study of modeling.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green