07w5079 Bioinformatics, Genetics and Stochastic Computation: Bridging the Gap

Arriving Sunday, July 1 and departing Friday, July 6, 2007

Organizers: Arnaud Doucet (University of British Columbia), Raphael Gottardo (University of British Columbia), Christian Robert (Ceremade, Universite Paris Dauphine).

Confirmed Participants

Press Release: World's Experts on Bioinformatics, Genetics and Stochastic Computation Meet at BIRS

Information for Participants

Schedule and Abstracts (PDF file)

Mailing List

Final Report (PDF file)

Objectives

On the one hand, there is an explosion of complex statistical models appearing in genetics and bioinformatics. These typically highly structured systems are unfortunately very difficult to fit. On the other hand, there has been recently significant advances on MC methods but most of these methods are unknown to the applied community and/or formulated in ways that are too theoretical for direct application. By providing scientists with improved inferential methods it would allow them to consider richer models, which are more realistic than those dictated by computational constraints. The exchanges between the applied and methodological communities remain surprisingly limited.

We believe that this workshop would be an ideal place to (1) Gather people from different research communities and foster links between these communities (applied, methodological and theoretical). (2) Expose the applied community to novel statistical methodologies and advanced MC methods, and expose the MCMC community to the specifics of the complex modeling problems met in bioinformatics and genetics. (3) Classify topologies of computational problems met bioinformatics and genetics, and equip all participants to the workshop with benchmark problems, if possible before the workshop.

We anticipate this workshop to create an exceptional opportunity for exchanging ideas between the communities; and help to shape the future of stochastic computation within bioinformatics and genetics. Input from statisticians working in bioinformatics and genetics is absolutely crucial for development of appropriate statistical methodologies. We will encourage researchers to bring data from their own field, which could be used to implement methods and try new algorithms. We have targeted areas of stochastic computation that are of great interest to practitioners such as automatic algorithms, computational issues and parallel implementations. Bioinformatics and genetics are relatively new fields that enjoy a high representation of young talents, including many women. This workshop would be a great learning/training environment for these new talents.