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