Statistical Science for Genome Biology

The main objective for this workshop is to facilitate the development and dissemination of statistical methods relevant to genome-scale biology, by bringing together leading researchers working at the interface between the biological and mathematical sciences. An important goal, that is reflected in our list of proposed invitees, is to include statisticians working on different aspects of statistics but all related to genomics. We have intentionally targeted areas ranging from classical statistical genetics, such as the genetic mapping of complex traits, to the emerging area of high throughput gene and protein expression analysis. It is becoming increasingly important for statisticians working in genomics to be aware of the quantitative problems and solutions related to diverse experimental platforms. Biological investigators are taking advantage of opportunities to study a system or process from several angles simultaneously and there is a growing need for quantitative methods to handle disparate data types seamlessly, for example, a holistic analysis based on sequence, expression, and molecular interaction data. An aim of this workshop is to devise appropriate statistical formulations for such analyses, which will expedite the creation and application of sound and powerful statistical methodologies.

The utility of sophisticated statistical methods in modern biology is well-established and has been addressed in more detail elsewhere in this proposal. Promoting genomics as a source of interesting and important problems is also of great benefit to the statistics research community. The fascinating developments in the biological sciences have generated an unprecedented enthusiasm in the computational sciences generally (statistics, mathematics, and computer science) by raising novel and challenging methodological questions. However, there can be significant 'barriers to entry and expansion' in this type of interdisciplinary work. This workshop would enable researching statisticians, with documented expertise and interest in genomics, to broaden their knowledge of current research and important open problems.

The question of timeliness is quite easy to address in this case. The pace at which genomic data are accumulating far exceeds the scientific community's ability to interpret it. Likewise, the emerging subspecialty in statistics -- statistical genetics and genomics -- is growing and changing rapidly and a workshop specifically aimed at this area is sorely needed.

Confirmed Participants

Schedule (pdf file)