Molecular Programming with Stochastic Pi Calculus: Computer Representation of Biological Processes

The ability to encode, share and update knowledge in a computable way is the primary cause for the rapid advance in the ``sequence'' and ``structure'' branches of Biology. In contrast, the complex knowledge on biological ``function'' and ``process'' is shared primarily via text and figures of scientific articles. The impact of finding a computer language suitable for its encoding cannot be overestimated.

In our research we use a stochastic extension of the Pi Calculus for representing and simulating biological processes. We were able to encode with surprising ease an entire spectrum of molecular systems --- core examples taken from chemistry, organic chemistry, biochemistry, and molecular cell biology --- with a uniform and compositional methodology. The resulting programs are simple and concise, they employ the same terms and concepts used in the scientific literature and the same level of abstraction, and they are executable, providing working simulations of the specified molecular systems. Our experience suggests that stochastic Pi Calculus may serve as a framework for encoding process knowledge in Biology, similarly to the way the formal languages of strings and labeled 3D graphs serve the bioinformatics of sequence and structure.