Exploring Genomic Medicine Using Integrative Biology

Details

Date Thursday June 15th 2006
Time 4:00-5:00pm
Venue George E. Pake Auditorium

PARC Forum

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 just 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, genomics, 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, representing the experimental context using a structured vocabulary has not yet happened, yet is a crucial step towards automated integrative biology. 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 using this coding that could not have been done before. 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 of the specificity, or lack thereof, of disease biomarkers.

Presenter(s)

Atul Butte, M.D., Ph.D. is an Assistant Professor in Medicine (Medical Informatics) and Pediatrics at the Stanford University School of Medicine, 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 30 presentations world-wide on bioinformatics, including nine at the National Institutes of Health or NIH-sponsored meetings. Dr. Butte's recent awards include the 2006 PhRMA Foundation Research Starter Grant in Informatics, the 2003 Emory University School of Medicine Pathology Residents' Choice Award, the 2002 and 2003 American Association for Clinical Chemistry Outstanding Speaker Award, the 2002 Endocrine Society Travel Award based on presentation merit, the 2001 American Association for Cancer Research Scholar-In-Training Award and the 2001 Lawson Wilkins Pediatric Endocrine Society Clinical Scholar Award. Dr. Butte's research is supported by grants from NIDDK and NLM. 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.

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