Process Algebra Models in Biology

Abstract

Process algebras are formal languages, which were originally designed to study the properties of complex reactive computer systems. Due to highly parallelized interactions and stochasticity inherit in biological systems, programming languages that implement stochastic extensions of processes algebras are gaining increasing attention as modeling and simulation tools in systems biology. The author discusses stochastic process algebras from the point of view of their broader potential as unifying instruments in systems biology. They argue that process algebras can help to complement conventional more established approaches to systems biology with new insights that emerge from computer science and software engineering. Along these lines, the author illustrates on examples their capability of addressing a spectrum of otherwise challenging biological phenomena, and their capacity to provide novel techniques and tools for modeling and analysis of biological systems. For the example models, they resort to phagocytosis, an evolutionarily conserved process by which cells engulf larger particles.