Stochastic Simulation Service: Bridging the gap between the computational expert and the biologist

Andreas Hellander
Division of Scientific Computing
Department of Information Technology
Uppsala University


Discrete stochastic simulation has become an important and widely-used tool for modeling of biological systems at the molecular scale. At the same time, there has been no single place where one can go to develop a discrete stochastic model with increasing levels of complexity: from the early stages, where it may begin as an ODE model, to a well-mixed (spatially homogeneous) discrete stochastic model, to a spatially inhomogeneous stochastic model with complex geometry and multiple internal surfaces, and finally to a spatially inhomogeneous stochastic model where single molecules at a microscopic level may interact with molecules modeled mesoscopically. The focus of the StochSS project, which has been going on for the last 5 years as a collaboration between The Petzold and Krintz groups at UCSB and the Systems Biology group at UU, has been to build such a place: an integrated development environment featuring state of the art algorithms as well as a means for the community to add new algorithms and capabilities, supported on a wide range of hardware from desktop workstations to high-performance clusters in the cloud. In this talk I will describe a selection of the computational and theoretical challenges of the stochastic simulations supported StochSS, and I will demonstrate the current version of the software. If time permits, I will also describe how we have been working on this distributed OpenSource project and share some experiences of collaborative software development.