Functional genomics represents a new phase of genome analysis. It refers to the development and application of global experimental approaches to assess gene function. It is characterized by high throughput or large-scale experimental methodologies combined with statistical and computational analysis of the results. The fundamental strategy in a functional genomics approach is to expand the scope of biological investigation from studying single genes or proteins to studying all genes or proteins at once in a systematic fashion. Sophisticated statistical and computational techniques are required to analyze responses of thousands of genes in order to identify interesting genes or clusters of genes. E.g. by examining the level of gene expression in cell populations of disease and pre-disease states, investigators will attempt to understand the steps of disease development and to identify the genes involved in disease susceptibility and gene-environment interactions.

The track focuses on new statistical and computational topics in functional genomics and expression array analysis.