ISMB99 Tutorial Material
Making the most of your hidden Markov models
This tutorial is intended for people who know what an HMM is but want
to know how to use them most effectively. It details the tricks used
in the SAM-T98 method (in 1998 the best method for remote homology
detection in proteins). One feature of this tutorial is the use of
sequence logos on a running example to show how various operations
change what is being searched for.
- Presentation material
- Introductory material on hidden Markov models
- Performance of hidden Markov models
``Sequence comparisons using multiple sequences detect three times as many
remote homologues as pairwise methods''
Jong Park, Kevin Karplus, Christian Barrett, Richard Hughey, David Haussler,
Tim Hubbard, and Cyrus Chothia, JMB 284(4):1201-1210, 1998
``hidden Markov models for detecting remote protein homologies''
Kevin Karplus, Christian Barrett, and Richard Hughey,
Bioinformatics 14(10):846-856, 1998
``Predicting protein structure using only sequence information'', by
Kevin Karplus, Christian Barrett, Melissa Cline, Mark Diekhans, Leslie Grate,
and Richard Hughey, Proteins: Structure, Function, and Genetics
(to appear in 1999).
- Null models, regularizers, and other accessory material
``Scoring hidden Marov models''
Christian Barrett, Richard Hughey, and Kevin Karplus,
CABIOS, 13(2):191-199, 1997.
``Dirichlet mixtures: a method for improved detection of weak but
significant protein sequence homology''
Kimmen Sjölander, Kevin Karplus, Michael Brown, Richard Hughey,
Anders Krogh, I. Saira Mian, and David Haussler,
CABIOS, 12(4):327-345, August 1996.
``Evaluating regularizers for estimating distributions of amino acids''
Kevin Karplus, In ISMB-95, Menlo Park, CA, July 1995. AAAI/MIT Press.
- Other Material
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Last modified: Wednesday July 21 1999