Using Hybrid Concurrent Constraint Programming to Model Dynamic Biological Systems

Systems biology is a new area in biology that aims at achieving a systems-level understanding of biological systems. While current genome projects provide a huge amount of data on genes or proteins, lots of research is still necessary to understand how the different parts of a biological system interact in order to perform complex biological functions. Computational models that help to analyze, explain or predict the behavior of biological systems play a crucial role in systems biology. The goal of this paper is to show that hybrid concurrent constraint programming [11] may be a promising alternative to existing modeling approaches in systems biology. Hybrid cc is a declarative compositional programming language with a well-defined semantics. It allows one to model and simulate the dynamics of hybrid systems, which exhibit both discrete and continuous change. We show that Hybrid cc can be used naturally to model a variety of biological phenomena, such as reaching thresholds, kinetics, gene interaction or biological pathways.

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