Individual Genomes Reveal Deep Population Histories and Uncover the Evolutionary Rolesof Non Coding DNA, Part 1
February 18, 2014
12:30 PM - 01:30 PM
Goergen Hall, Room 101
High throughput DNA sequencing has lead to a surge of genomic data, which is expected to revolutionize our knowledge of evolution and genomic function. In this talk, I will introduce some of the tough computational challenges we face when trying to make use of these rich data sets to resolve open questions in evolution. The talk will focus on methods I developed to reconstruct population histories and quantify the effect of recent natural selection using complete individual genome sequences. I will present work I did in utilizing these methods to discover deep splits in human population history, investigate the origins of domestic dogs, and examine the contribution of non coding regulatory elements to recent evolution of the human genome. I will conclude with a short survey of my ongoing research, and a map of the opportunities and challenges we face in the study of evolution in a world of rapidly evolving genomic data sets.
Ilan Gronau is a computational biologist studying evolution and population genetics. He received his PhD from the Computer Science department at the Technion and has a Masters degree in Bioinformatics from the Weizmann Institute. Since 2009, he has been a postdoctoral fellow in Adam Siepel's computational genomics lab in Cornell. Ilan develops computational methods for solving a wide range of fundamental evolutionary inference problems, such as phylogenetic reconstruction, demography inference, and detection of recent natural selection. His work combines innovative computational approaches and cutting edge genomic data sets to examine central open questions in evolution.
Host: Jack Werren