home · mobile · calendar · colloquia · 2008-2009 · 

Colloquium - Eddy

Next Generation Homology Search Tools -- Beyond BLAST
Howard Hughes Medical Institute

Database homology searching may be the most important application in computational molecular biology, and since the 1990s, BLAST has been our main workhorse. Since BLAST's introduction, theoretical advances have been made in applying more formal probabilistic inference to homology searches using hidden Markov model (HMM) approaches. General adoption of these methods has been limited by some key problems, including the fact that the popular HMM implementations (including my HMMER software) are computationally demanding.

I will describe HMMER3, a new generation of HMMER that aims to more fully apply probabilistic inference to homology searches, while at the same time attaining BLAST's speed. I will describe HMMER3's statistical inference approach, its probabilistic model of local sequence alignment, new statistical theory for log-likelihood ratio scores that extends Karlin/Altschul theory for optimal alignment scores, and an implementation that has accelerated HMMER3 100-fold relative to HMMER2.

Sponsored by the Department of Chemistry and Biochemistry.

Department of Computer Science
University of Colorado Boulder
Boulder, CO 80309-0430 USA
May 5, 2012 (14:13)