Speaker: Oliver Hampton, graduate student in CS department
Time & location: 4/2/04 Friday at 11am in SH124

Title:

Highly Specific Protein Function Classification Using Hidden Markov
Models

Abstract:

Hidden Markov models are a class of statistical models based of
probability. Historically, hidden Markov models have been applied in
speech recognition, but also suffice as representations of linear
biological sequence information. Unlike pairwise sequence alignment search
techniques, hidden Markov models are adept at remote homology detection
and are particularly well suited for identifying evolutionary distant
biological sequences. In this talk, the advantages of hidden Markov
model search capabilities are exploited for the functional annotation of
uncharacterized proteins.