Stefan Hellander joins the lab

  We are delighted to have Stefan Hellander join the lab!  Stefan obtained his Ph.D. in scientific computing from Uppsala University in 2013, with the thesis “Stochastic Simulation of Reaction-Diffusion Processes”, advised by Prof. Em. Per Lötstedt. He then went on to work as a postdoc in the lab of Prof. Linda Petzold at UCSB, […]

Fredrik Wrede presented at MLSB 2017

Fredrik Wrede presented a poster titled “Smart systems for model exploration with application in computational systems biology” at the Machine Learning in Systems Biology  (MSLB) 2017 Workshop held as a special session of ISMB 2017, Prague, Czech Republic, on July 25, 2017.

Hierarchical Analysis of Spatial and Temporal Data

The HASTE project, a SSF-funded project on computational science and big data, takes a holistic approach to new, intelligent ways of processing and managing very large amounts of microscopy images to leverage the imminent explosion of image data from modern experimental setups in the biosciences. One central idea is to represent datasets as intelligently formed […]

HASTE is granted 29 MSEK funding from SSF

Our project Hierarchical Analysis of Spatial and TEmporal Data (HASTE) is granted 29 MSEK funding from SSF. The project, with PI Carolina Wählby  and co-PIs Andreas Hellander, Ola Spjuth and Mats Nilsson, will explore new ways to gain insight from massive amounts of spatial and temoral image data through hierarchical analysis models and smart cloud systems […]

Scalable simulation of stochastic multicellular systems

In multicellular systems, cells of different types interact in various ways, both mechanically and chemically, to regulate complex processes. There is a large computational gap between detailed models of sub-cellular, molecular processes in single cells, and models of multicellular systems comprising of large numbers of interacting cells such as bacterial colonies, tissue and tumors. In […]

Model exploration using active learning

The exploration of a system described by a non-linear, high-dimensional and stochastic computational model is a fundamental problem in all scientific disciplines relying on modeling and simulation.  In this project we are interested in the scenario where a modeler has no or very limited prior knowledge about what type of qualitative interesting behavior the model […]

StochSS: Stochastic Simulation Service

StochSS is an integrated development environment (IDE) for discrete stochastic biochemical simulations. Users make use of a graphical user interface (GUI) to define their problem, including its domain (geometry, volume), molecular interactions (stoichiometry, rate constants), and simulation goals (single trajectory, histogram, probabilities of rare events). The platform transparently executes model workflows using local resources (laptops, […]

Multiscale simulations of chemical kinetics

Life spans in size from small organisms consisting of single cells to complex organisms built up of billions of cells. Even the single-cell organisms are challenging to fully understand and study—their function is dependent on a rich set of reaction networks. Important molecules inside a cell may exist in only a few copies, and that […]