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Finding genes in large genomes
Student-Run Research| Speaker: | Lior Pachter, UC Berkeley |
| Location: | 693 Kerr |
| Start time: | Tue, Feb 6 2001, 12:10PM |
Description
ABSTRACT: The study of molecular biology on a whole genome scale has only
recently become possible as a result of the many ongoing genome
sequencing projects. In order to understand the relationship between
sequences and their biological function it is helpful to accurately
annotate the sequences, but this problem has proved to be very
difficult. Another approach for extracting information from the
sequences is to compare and contrast them. In this way it is possible
to infer information about a newly sequenced organism by extrapolating
from what is known about another (this is similar to the way the
Rosetta stone was used to decipher Egyptian hieroglyphics using
ancient Greek).
We will review the mathematical tools used for similarity searching
(alignment), and for annotation (gene recognition). We will then show
that hidden Markov models provide a probabilistically sound theory for
unifying and generalizing classical results about the two problems.
