The role of Bioinformatics in teasing apart epigenetics in cancer (Event Details)
Speaker: Kimberly J. Bussey, Ph.D., Associate Investigator in the Clinical Translational Research Division, Lead Investigator of the Adrenocortical Carcinoma (ACC) Research Program at TGen
Location: Biodesign Auditorium
Date & Time: March 25, 2010 12:00 p.m.
Title: The role of Bioinformatics in teasing apart epigenetics in cancer
The role of Bioinformatics in teasing apart epigenetics in cancer
The epigenome refers to heritable and reversible marks in the genome that do not result from changes in DNA sequence. These include modifications of DNA and/or histones such as methylation, acetylation, sumolation, and ubiquitination, as well as the region-specific incorporation of variant histone proteins. Recent work has highlighted the importance of the epigenome in regulating gene expression and contributing to phenotypic heterogeneity. The number and types of data being generated to look at various aspects of the epigenome is rapidly expanding and requires the adaptation of existing bioinformatics approaches or more commonly the development of new approaches. We will discuss where the field of epigenomics is currently, both experimentally and bioinformatically, and what questions need to be addressed, particularly as they relate to cancer.
Kim’s Biosketch: Dr. Bussey received her B.S. in general biology from the University of Arizona. She received her Ph.D. in Molecular and Medical Genetics from Oregon Health Sciences University where her dissertation research focused on the cytogenetic and molecular characterization of pediatric germ cell tumors, a group of rare tumors in children. Prior to coming to TGen as an Associate Investigator and Lead Investigator for the ACC Research Program, she did a post-doctoral fellowship and worked as a contract scientist with John Weinstein, M.D., Ph.D. and the Genomics and Bioinformatics lab in the Laboratory of Molecular Pharmacology at the NCI. Her work there focused on integrative analysis of array CGH data and expression data in the NCI60 and development of computational tools to facilitate such analyses.