Workshop on Statistical Learning of Biological Systems from Perturbations
This workshop will be held in Ascona, Switzerland, May 31 to June 5, 2015.
Advances in biotechnology have made genome-scale measurements routine, including most recent techniques for perturbing individual genes in a targeted manner. These interventional data hold the promise to infer biological networks and to move forward systems biological approaches significantly. A major challenge now is to use the vast amount of data generated from these technologies and to devise appropriate statistical models and computational inference methods. Unlike observational data, interventional data can reveal causal relationships among genes or other biomolecular entities. As such, the statistical analysis and computational integration of perturbation data is an important step towards large-scale biological system identification with abundant applications in biology and medicine.
This workshop will (i) explore recent advances and open problems in statistical learning, data integration, and causal inference of biological systems; (ii) present biomedical applications to recent genome-wide perturbation data, such as RNA interference data, obtained, for example, from cancer cells or cells infected by pathogens; and (iii) facilitate meaningful interaction between biomedical and quantitative researchers.
Confirmed invited speakers: Brenda Andrews (Donnelly Centre), Alexis Battle (Johns Hopkins University), Roderick Beijersbergen (Netherlands Cancer Institute), Michael Boutros (DKFZ, Heidelberg), Anne Carpenter (Broad Institute), Bernd Fischer (EMBL/DKFZ Heidelberg), Susan Holmes (Stanford), Marloes Maathuis (ETH Zurich), George Michailidis (University of Michigan), Lars Steinmetz (EMBL Heidelberg and Stanford).
Contributed presentations are also welcome.
More details and pre-registration instructions are available at http://www.cbg.ethz.ch/news/ascona2015
Pre-registration is mandatory and closes 6 February 2015.
Seminar für Statistik
Tel: +41 446326518 Fax: +41 446321228
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