The Butte Lab

Translational bioinformatics has been defined as the development of analytic, storage, and interpretive methods to optimize the transformation of increasingly voluminous genomic and biological data into diagnostics and therapeutics for the clinician.

The long-term research goal of the Butte Lab is to develop translational bioinformatics methods to reason over many available genome-scale measurement and experimental modalities, and apply these methods to study complex disorders in genomic medicine, especially obesity and type 2 diabetes mellitus.

The Butte Lab has three main directions in exploring translational bioinformatics. First, we have developed bioinformatics methods to integrate genomic, genetic, phenotypic, clinical, and gene-knockout data from multiple sources and phenotypes and reason over these data. An example of this was our recent work on fat cell formation published in Nature Cell Biology (2005) and on obesity in Bioinformatics (2007, in press). Second, we have developed tools to automatically index and find genomic and proteomic data sets based on the phenotypic and contextual details of each experiment. We used these tools to create a comprehensive phenome-genome network published in Nature Biotechnology (2006). Third, we are building a novel gene-expression-based classification scheme for diseases across the entire field of medicine. Initial work on this will appear in Nature Methods (2007, in press).