The long-term research goal of the Butte Lab is to solve problems relevant to genomic medicine by developing new methodologies in translational bioinformatics.
First, we have developed bioinformatics methods to take genomic, genetic, phenotypic, and RNAi data from multiple sources and phenotypes and reason over these data. An example of this was in our work in cancer drug discovery published in the Proceedings of the National Academy of Science (2000), on type 2 diabetes mellitus published in the Proceedings of the National Academy of Science (2003), on fat cell formation published in Nature Cell Biology (2005), on obesity in Bioinformatics (2007), and in transplantation published in Proceedings of the National Academy of Science (2009). Second, we have developed tools to automatically index and find genomic data sets based on the phenotypic and contextual details of each experiment. Our work on automatic annotations of the data in the NCBI Gene Expression Omnibus was published in Nature Biotechnology (2006), our work in re-mapping microarray data was published in Nature Methods (2007), and our work in deconvolution of whole blood expression was published in Nature Methods (2010). Third, we have been developing some novel methods in comparing clinical data from electronic health record systems with gene expression data, as described in Science (2008), using genetic measurements, as described in PLoS Genetics (2010), and using gene-expression data, as described in Molecular Systems Biology (2009), and described in PLoS Computational Biology (2010), and described in the New York Times and International Herald Tribune.
The Butte Lab is in the Stanford Department of Pediatrics in the Stanford University School of Medicine, and is a core faculty laboratory in the Biomedical Informatics Training Program at Stanford University. The Butte Lab also serves as the Center for Pediatric Bioinformatics at Lucile Packard Children's Hospital. The Butte Lab is also affiliated with the Stanford Center for Biomedical Informatics Research (formally Stanford Medical Informatics or SMI).