Center for Computational Molecular Biology Faculty Search Candidate
"Combinatorial Methods in Evoluntionary Biology"
Nicholas Eriksson, Ph.D., University of Chicago, Department of Statistics
Monday, March 3, 2008 at 4:00 P.M.
Room 241 Swig Boardroom (2nd Floor CIT)
I'll talk about three areas of evolutionary biology using a combination of statistics and discrete math: viral population diversity, the evolution of drug resistance, and phylogenetics.
Knowledge of the diversity of viral populations is important for understanding disease progression, vaccine design, and drug resistance, yet it is poorly understood. New technologies (pyrosequencing) allow us to read short, error-prone DNA sequences from an entire population at once. I will show how to assemble the reads into genomes using graph theory, allowing us to determine the population structure.
Next, I will describe a new class of graphical models inspired by poset theory that describe the accumulation of (genetic) events with constraints on the order of occurrence. Applications of these models include calculating the risk of drug resistance in HIV and understanding cancer progression.
Finally, I'll describe a polyhedral method for determining the sensitivity of phylogenetic algorithms to changes in the parameters. We will analyze several datasets where small changes in parameters lead to completely different trees and see how discrete geometry can be used to average out the uncertainty in parameter choice.
Host: Charles Lawrence
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