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CCB Seminar: Sequence homology searches – the future of deciphering the past

March 1 @ 1:00 pm - 2:00 pm

Dr. Sean Eddy, Professor, Molecular and Cellular Biology, Harvard University
Abstract:
Computational recognition of distant sequence homology is a key to
studying ancient events in molecular evolution. The better our
sequence analysis methods are, the deeper in evolutionary time we can
see. A major aim in the field is to improve the resolution of homology
recognition methods by building increasingly realistic, complex,
parameter-rich models. I will describe current and future research in
homology search algorithms based on probabilistic inference methods,
including hidden Markov models (HMMs) and stochastic context-free
grammars (SCFGs). We make these methods available in the HMMER and Infernal software from my laboratory, in collaboration with sequence family databases including Pfam and Rfam.
Biography:
Sean Eddy is a computational biologist at Harvard University. Before
moving to Harvard in 2015, he was a group leader at the Howard Hughes
Medical Institute’s Janelia Research Campus, and before that, a
faculty member in the Genetics department at Washington University in
St. Louis. He received a bachelor’s degree from Caltech, a Ph.D. from
the University of Colorado at Boulder, and did postdoctoral work at
NeXagen in Boulder and at the MRC Laboratory of Molecular Biology in
Cambridge, UK.

Details

Date:
March 1
Time:
1:00 pm - 2:00 pm
View Event Website

Venue

Zoom Seminar