BlenX-based compositional modeling of complex reaction mechanisms

TL;DR

This paper introduces a compositional modeling approach using the BlenX language to simulate complex biological reaction mechanisms, addressing the challenge of combinatorial explosion in biological networks.

Contribution

It demonstrates how to systematically unpack complex reactions into BlenX templates and discusses parameter estimation challenges in stochastic models.

Findings

Successful modeling of a circadian clock example

Effective decomposition of complex reactions into BlenX templates

Discussion on parameter estimation in stochastic frameworks

Abstract

Molecular interactions are wired in a fascinating way resulting in complex behavior of biological systems. Theoretical modeling provides a useful framework for understanding the dynamics and the function of such networks. The complexity of the biological networks calls for conceptual tools that manage the combinatorial explosion of the set of possible interactions. A suitable conceptual tool to attack complexity is compositionality, already successfully 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 simulate high-level descriptions of biological circuits. The Gillespie's stochastic framework of BlenX requires the decomposition of phenomenological functions into basic elementary reactions. Systematic unpacking of complex reaction mechanisms into BlenX templates is shown in this study. 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 BlenX compositionality.