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Network Analysis of Stem Cell Data for Human Toxicology

Reference number
SM10-0019
Start and end dates
110101-121231
Amount granted
1 350 000 SEK
Administrative organization
Cellartis AB
Research area
Life Science Technology

Summary

We aim to develop a predictive model of the underlying gene regulatory network relevant to human developmental toxicity using recent advances in machine learning (ML) techniques, especially in probabilistic graphical models. We start with previously identified underlying core network of protein-protein interactions and superimpose on this dynamic time series data of gene expressions generated by Cellartis. ML techniques are then employed to infer how the strengths of interactions in the underlying network change in time and to isolate coherently acting modules and sub-networks. This will then be used to design further experimental assays on a much smaller subset of genes to test and screen reactions to different chemical compounds. We expect the work to be carried out initially in a combination of local masters projects at Chalmers and collaborations with the Life Sciences division of Persistent Systems, a IT company based in India. Later we hope to develop competence at the Ph.D. level, possibly via "industridoktorand" positions between Chalmers and Cellartis.

Popular science description

One of the most exciting new developments in research today in Biology and Medicine is stem cells. These are cells that have the capability to reproduce indefinitely or to specialize into any fo the thousnads of different cells in our bodies. because of these remarkable properties, they hold keys to understanding the basic mechanisms in how a newly born embryo develops into an adult, and also unimaginable possibilites for new approaches and techniques in medical therapy. for example, new drugs can be tested in various contexts, or, remarkably, damaged cells and tissues may be repaired by injecting such cells. To realise this, the basic genetic mechanisms underlying stem cell behaviour needs to be better understood. The goal of the project is to contribute to this by developing mathematical and computational models of stem cells in close collaboration with experimentalists at Cellartis. The visit is of potential benefit to both parties. Chalmers has recently identified Life Sciences as one of its core prioritized areas for research and education. Contact with a leading Biotech company would greatly enrich its activites in this area. Cellartis would benefit from contact with Chalmers expertise in computational modelling and from good masters and Ph.D. students carrying out thesis work with them.Such university-industry exchanges are widely believed to be absoluately necessary for the renewal and vigorous strategic development of reseach. education and innovation in Sweden