Statistical Genomics

The fields of statistics, genetics, and agriculture share a long history of mutual benefit that has recently been reaffirmed through advances in molecular genetics, genomics, and bioinformatics. This resurgence has forged cooperative connections among mathematics, statistics, computer science, and biology that are fueled by technological advances -- in short, to a new interdisciplinary approach to biology.

Additionally, these rapid advances have radically changed the amount and type of information available for the characterization of genes. In many genomic applications, existing methodologies coupled with powerful computing have successfully directed the exploration of highly dimensional and rich data collections.

What remains to be accomplished is the successful statistical modeling of biological phenomena for the purpose of supporting hypothesis-driven biology. This will ultimately tap into the predictive wealth that much of the current and impending genomic data has the potential to offer. Statistical development will continue to significantly amplify and focus the molecular advances of the last 20 years toward general improvements in agriculture and human health.

As databases for agricultural species continue to grow, agricultural genomics presents tremendous opportunities for success. Our dynamic faculty (Aref, Doerge, McIntyre, Simonsen, Xie) are taking advantage of these opportunities and, in the process, creating an exciting environment for research and education.

The formation of a new center in statistical bioinformatics is expected to provide additinal momentum to these endeavors.