The Computational and Statistical Genomics focus area promotes computational, mathematical, and statistical research, development, and education associated with the development of highly advanced tools for data acquisition and analysis, in order to understand the origins of life and the molecular processes that underlie both the unity and the diversity of life. Genome sequences reveal the complete gene repertoire of diverse organisms and provide new insights into organisms as complex systems. The amount and speed of data acquisition requires computational approaches to gene prediction. The high diversity and complexity of proteins encoded in genomes (the so-called "proteome") leads to a need for computational approaches to protein folding, assembly, and inference of function as powerful complements to empirical analysis. Comparisons among different species in the context of a well-resolved evolutionary tree provide essential insights into gene function, into pathways by which genes and genomes evolve, and into mechanisms that shape genetic diversity. The ability to move between organisms on the threads of common descent greatly accelerates both gene discovery and functional determination in laboratory "model" organisms and others for which medical or economic value or function is of particular importance.

Phase I accomplishments include the formation of the new Department of Biological Statistics and Computational Biology in the College of Agriculture and Life Sciences, creation of the Computational Biology Service Unit at the Cornell Theory Center, and establishment of new concentrations and interdisciplinary training programs at both the undergraduate and graduate levels. Four faculty were recruited (2 in Computer Science/Engineering, 2 in CALS): Ron Elber, Computational Structural Biology and Genomics (Computer Science/Engineering; Dept. Computer Science; from Hebrew University, Professor), Golan Yona, Computational Molecular Genomics (Computer Science/Engineering; Dept. Computer Science; from Stanford University, Asst. Prof.), Rasmus Nielsen, Statistical and Population Genomics (CALS; Dept. Biol. Stat. & Comp. Biol.; from Harvard, Asst. Prof.), and Carlos Bustamante (CALS; Dept. Biol. Stat. & Comp. Biol.; from Oxford, Asst. Prof.).

In Phase II, this focus area is contributing to the development of a statistical genomics core in the new Department of Biological Statistics and Computational Biology. Faculty recruitment is targeted to build teaching and research strength in the computer science aspects of computational genomics, and in the interface between statistical, computational, experimental, comparative, and evolutionary genomics. Active searches include Bioinformatics (university-wide) and Computational Biology (Computer Science), plus searches in the related areas of Human Genetics and Epidemiology (Human Ecology, Division of Nutrition). Proposed positions include a Chair plus three junior hires in Statistical and Computational Genomics in the Department of Biological Statistics and Computational Biology, a position in Computational Modeling of Cells (Engineering), and in the analysis of gene expression arrays and integration with other sources of biological information (department not determined). A new Biological Statistics Service Unit is also proposed in Department of Biological Statistics and Computational Biology that would emphasize statistical problems, complementing the Computational Biology Service Unit. Training grant support for graduate students and postdocs is being sought, as is additional support for programmers and other resources needed for long-term stability of the Computational Biology and Biological Statistics Service Units.