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Event Detail (Archived)

Sequence Homology Searches: The Future of Deciphering the Past

Peter H. Sellers Lecture

  • This event already took place in March 2019
  • Carson Family Auditorium (CRC)

Event Details

Type
Center for Studies in Physics and Biology Seminars
Speaker(s)
Sean Eddy, Ph.D., Ellmore C. Patterson Professor of Molecular and Cellular Biology and of Applied Mathematics, Harvard University; investigator, Howard Hughes Medical Institute
Open to
Public
Contact
Melanie Lee
Phone
(212) 327-8636
Sponsor
Melanie Lee
(212) 327-8636
leem@rockefeller.edu
Notes
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.


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