Computational and Statistical Genomics (06w5076)
Organizers
Jennifer Bryan (University of British Columbia)
Sandrine Dudoit (University of California, Berkeley)
Sunduz Keles (University of Wisconsin, Madison)
Katherine S. Pollard (University of California, Davis)
Mark van der Laan (University of California Berkeley)
Description
High-throughput biotechnologies, such as DNA microarrays, provide the unprecedented and extraordinary opportunity to investigate biological processes on a genomic-scale. The resulting biological discoveries have promising and profound implications in terms of basic science and public health. However, our ever-growing capacity to generate massive and diverse biological datasets has far outpaced our ability to analyze and interpret these data. The combined analysis of high-dimensional complex biological and medical datasets, of multiples types and from multiple sources, is stretching the limits of existing computational and statistical methods. Between July 8th and July 13th, 2006, leading statisticians and biologists will gather at the Banff International Research Station (BIRS) to discuss computational and statistical challenges in the analysis of high-throughput biomedical and genomic data.
The BIRS workshop "Computational and Statistical Genomics" is co-organized by Professors Jenny Bryan (University of British Columbia), Sandrine Dudoit (University of California, Berkeley), Sunduz Keles (University of Wisconsin Madison), and Katie Pollard (University of California, Davis). The main goals are to foster close and sustained collaborations between statisticians and biologists. Such interactions are essential to the sound translation of existing and emerging biological problems into computational and statistical questions and the development of analysis methods and software that will allow biologists and clinicians to get the most out of the wealth of data at their disposal in-house and on the WWW.
The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interactionas well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is administered by the Pacific Institute for the Mathematical Sciences, in collaboration with the Mathematics of Information Technology and Complex Systems Network (MITACS), the Berkeley-based Mathematical Science Research Institute (MSRI) and the Instituto de Matematicas at the Universidad Nacional Autonoma de Mexico (UNAM).
The BIRS workshop "Computational and Statistical Genomics" is co-organized by Professors Jenny Bryan (University of British Columbia), Sandrine Dudoit (University of California, Berkeley), Sunduz Keles (University of Wisconsin Madison), and Katie Pollard (University of California, Davis). The main goals are to foster close and sustained collaborations between statisticians and biologists. Such interactions are essential to the sound translation of existing and emerging biological problems into computational and statistical questions and the development of analysis methods and software that will allow biologists and clinicians to get the most out of the wealth of data at their disposal in-house and on the WWW.
The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interactionas well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is administered by the Pacific Institute for the Mathematical Sciences, in collaboration with the Mathematics of Information Technology and Complex Systems Network (MITACS), the Berkeley-based Mathematical Science Research Institute (MSRI) and the Instituto de Matematicas at the Universidad Nacional Autonoma de Mexico (UNAM).
