Speaker: Dr. Tandy Warnow, Department of Computer Science, University of Texas at Austin
Time: 4:00-5:00pm, Tuesday, May 19th, 2009
Place: 321 Stanley Hall
Abstract:
Molecular sequences evolve under processes that include substitutions,
insertions, and deletions (jointly called “indels”), as well as
other mechanisms (e.g., duplications and rearrangements). The inference of the
evolutionary history of these sequences has thus been performed in two stages:
the first estimates the alignment on the sequences, and the second estimates
the tree given that alignment. While such methods seem to work well on
relatively small datasets, these two-stage approaches can produce highly
incorrect trees and alignments when applied to large datasets, or ones that
evolve with many indels. In this talk, I will present a new method,
SATé, that my lab has been developing that uses maximum likelihood to
estimate the alignment and tree at the same time, and that can be used to
analyze datasets with up to 1000 sequences on a desktop in 24 hours. Our
study, using both real and simulated data, shows that this method produces much
more accurate trees than the current best methods.
Joint work with Kevin Liu, Sindhu Raghavan, Serita Nelesen, and Randy Linder.
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