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INSTITUTE for GENOMICS and BIOINFORMATICS and CENTER for MACHINE LEARNING and INTELLIGENT SYSTEMS
2012-2013 Seminar Series
William S. Noble, Ph.D.
Professor, Department of Genome Sciences, School of Medicine
Department of Computer Science and Engineering, College of Engineering
University of Washington
“The one-dimensional and three-dimensional structure of the genome”
Monday, April 15, 2013 – 1:00pm
6011 Donald Bren Hall (Bldg. 314) at UC Irvine
No cost to attend – Open to the public
Seating is on a first-come, first –served basis
Anyone wishing to meet with Dr. Noble is encouraged to contact Janet Ko
Abstract: A variety of molecular biology technologies have recently made it clear that the function of the genome in vivo is determined both by the linear sequences of nucleotides along the chromosome and the three-dimensional conformation of chromosomes within the nucleus. In this talk, I will describe computational and statistical methods that we have developed and applied to a variety of genomes, with the goal of characterizing genome architecture and function. In particular, we have used unsupervised and semisupervised machine learning methods to infer the linear state structure of the genome, as defined by a large panel of epigenetic data sets generated by the NIH ENCODE Consortium, and we have developed methods to assign statistical confidence and infer the 3D structure of genomes from Hi-C data.
About the Speaker: Dr. William Stafford Noble is Professor in the Department of Genome Sciences in the School of Medicine at the University of Washington where he has a joint appointment in the Department of Computer Science and Engineering in the College of Engineering. Previously he was a Sloan/DOE Postdoctoral Fellow with David Haussler at the University of California, Santa Cruz before he became an Assistant Professor in the Department of Computer Science at Columbia University. He graduated from Stanford University in 1991 with a degree in Symbolic Systems before receiving a Ph.D in computer science and cognitive science from UC San Diego in 1998. His research group develops and applies statistical and machine learning techniques for modeling and understanding biological processes at the molecular level. Noble is the recipient of an NSF CAREER award and is a Sloan Research Fellow.