BIOKDD '07 Invited Speakers

 Atul Butte, M.D., Ph.D.

Exploring Genomic Medicine Using Integrative Biology

The past 10 years have led to a variety of measurements tools in molecular biology that are nearly-comprehensive in nature. For example, microarrays are one of at least 30 large-scale measurement or experimental modalities available to investigators in molecular biology. Instead of focusing on the cell, or the genotype, or on any single measurement modality, using integrative biology allows us to think holistically and horizontally. A disease like diabetes can lead to myocardial infarction, nephropathy, and neuropathy; to study diabetes in genomic medicine would require reasoning from a disease to all its various complications to the genome and back. To enable such research, we have been studying the process of intersecting genome-scale data sets in molecular biology, such as those from genetics, microarrays, knockout experiments, and many others. I will show how we have built computational tools that reason over these types of data to help enable discoveries in genomic medicine, with specific applications for obesity and diabetes mellitus. Though standards are increasingly being required and used for genome-scale data, integrative biology is hampered by the lack of standards for representing the experimental context of an experiment. I will show how the largest unified biomedical vocabulary can now be used to represent microarray sample annotations and show examples of visualization, searching, and analysis across microarray experiments using this coding that could not have been done before. Finally, I will end with a consideration of ways we can use genome-scale data to provide new ways to classify disease, and show how this broad recasting of disease nosology allows identification of new therapeutic opportunities and disease biomarkers.

Biography

Atul Butte, M.D., Ph.D. is an Assistant Professor in Medicine (Medical Informatics) and Pediatrics at the Stanford University School of Medicine and the Lucile Packard Children's Hospital, and a board-certified pediatric endocrinologist. Dr. Butte received his undergraduate degree in Computer Science from Brown University in 1991, and worked in several stints as a software engineer at Apple Computer (on the System 7 team) and Microsoft Corporation (on the Excel team). He graduated from the Brown University School of Medicine in 1995, during which he worked as a research fellow at NIDDK through the Howard Hughes/NIH Research Scholars Program. He completed his residency in Pediatrics and Fellowship in Pediatric Endocrinology in 2001, both at Children's Hospital, Boston. Dr. Butte received a Ph.D. in Health Sciences and Technology from the Medical Engineering / Medical Physics Program in the Division of Health Sciences and Technology, at Harvard Medical School and Massachusetts Institute of Technology.

Dr. Butte's laboratory focuses on solving problems relevant to genomic medicine by developing new biomedical-informatics methodologies in integrative biology. Dr. Butte has authored more than 25 publications in bioinformatics, medical informatics, and molecular diabetes and has delivered more than 35 presentations world-wide on bioinformatics, including nine at the National Institutes of Health or NIH-sponsored meetings. Along with Isaac Kohane and Alvin Kho, Dr. Butte has co-authored one of the first books on microarray analysis titled "Microarrays for an Integrative Genomics" published by MIT Press. Dr. Butte's recent awards include the 2007 Genome Technology "Tomorrow's Principal Investigator" Award, the 2006 Howard Hughes Medical Institute Early Career Award, the 2006 PhRMA Foundation Research Starter Grant in Informatics, the 2002 and 2003 American Association for Clinical Chemistry Outstanding Speaker Award, and the 2001 Lawson Wilkins Pediatric Endocrine Society Clinical Scholar Award. Dr. Butte's research is supported by grants from the Howard Hughes Medical Institute, the National Library of Medicine, the National Institute for General Medical Science, and the National Human Genome Research Institute.