Yun S. Song

University of California, Berkeley

Central to many applications in genetic analysis is the notion of sampling distribution, which describes the probability of observing a sample of DNA sequences randomly drawn from a population.  In the one-locus case with special models of mutation, closed-form sampling distributions have been known for many decades.  For example, the so-called infinite-alleles model admits a closed-form sampling formula which also arises in several interesting contexts outside biology, including size-biased random permutations and factorizations of polynomials over a finite field.  However, no exact sampling formula is currently known for general models of mutation that are of biological interest.  Furthermore, things become substantially more complicated when recombination is taken into account.  In multi-locus models with finite recombination rates, finding an exact, analytic sampling distribution has so far remained a challenging open problem, even for the simplest case of two loci with the infinite-alleles model at each locus.


In this talk, I will revisit the aforementioned classical open problems in population genetics and discuss how progress can be made by borrowing ideas from computer science, physics, and combinatorics.  If time permits, I will describe applications of our work to estimating fine-scale recombination rates in Drosophila melanogaster, for which the average population-scaled recombination rate is about 20 to 30 times higher than that of humans.



Yun S. Song is an associate professor of EECS and Statistics at UC Berkeley. He received the BS degrees in mathematics and physics from MIT, and a PhD in theoretical physics from Stanford University.  Over the past decade he has been carrying out interdisciplinary research, with a focus on computational and mathematical biology.  In particular, he is interested in developing efficient computational methods for tackling important problems that arise from evolutionary biology.


B17 Upson Hall

Thursday, November 3, 2011

Refreshments at 3:45pm in the Upson 4th Floor Atrium


Computer Science


Spring 2011

A Fresh Computational Look into Classical Open Problems in Evolutionary Biology