FEDn is a framwork for scalable federated machine learning. The project is a collaboration with our spin-off Scaleout.


StochSS is cloud service for modeling and analyzing biological systems. https://github.com/StochSS/stochss


Sciope is a Python3 package supporting ML-assisted model exploration of stochastic biochemical reaction networks. It is part of the StochSS Suite of Software.

HASTE Toolkit

HASTE Tookit is a collection of tools enabling rapid construction of cloud-native, intelligent data pipelines following the model developed in the HASTE Project.

20 repositories, 0 followers.


PyURDME is a modeling and simulation toolkit for spatial stochastic simulations. It makes use of a modified version of the core solver of URDME (www.urdme.org) for mesocopic simulations via the Reaction-Diffusion Master Equation (RDME), and builds on Dolfin/FeniCS (http://fenicsproject.org) for geometric modeling, meshing and Finite Element Assembly. pyURDME only rely on open-source dependencies, and offer an object-oriented pythonic API to construct and simulate models.

MOLNs: Interactive Computational Experiments

MOLNs is a cloud appliance that will set up, start and manage a virtual platform for scalable, distributed computational experiments using (spatial) stochastic simulation software such as PyURDME (www.pyurdme.org) and StochKit/Gillespy (www.github.com/Gillespy/gillespy). In addition, MOLNs by default makes FEniCS/Dolfin available as-a Service.

Since MOLNs will configure and manage a virtual IPython Cluster (with a Notebook frontend), with Numpy, SciPy and Ipython Parallel enabled, it can also be useful for general contextualization and management of dynamic, cloud-agnostic (supports EC2 and OpenStack-based clouds) virtual IPython environments, even if you are not into spatial stochastic simulations in systems biology.


The Stochastic Simulation Algorithm (SSA) due to Gillespie is widely used to simulate biochemical reaction networks modeled as a continuous-time discrete-space Markov process. CellMC is an XSLT-based, automated SBML (Systems Biology Markup Language) model compiler capable of producing very efficient SSA executables for the Cell/BE or multicore x86 PCs. CellMC was developed by Emmet Caulfield as a part of his master’s thesis: “CellMC: An XSLT-based SBML model compiler for Cell/BE and IA32′. CellMC is no longer maintained but can still be obtained from www.cellmc.org .