Bioinformatics Advance Access originally published online on March 25, 2004
Bioinformatics 2004 20(14):2175-2180; doi:10.1093/bioinformatics/bth181
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Bioinformatics 20(14) © Oxford University Press 2004; all rights reserved.
Performance of an iterated T-HMM for homology detection
1 Biophysics Research Division, University of Michigan, Ann Arbor, MI 48109-1055, USA and 2 Division of Mathematical Biology, National Institute for Medical Research, The Ridgeway, Mill Hill, London, NW7 1AA, UK
Received on August 14, 2003; revised on March 1, 2004; accepted on March 3, 2004
Advance Access Publication March 25, 2004
Motivation: Much information about new protein sequences is derived from identifying homologous proteins. Such tasks are difficult when the evolutionary relationships are distant. Some modern methods achieve better results by building a model of a set of related sequences, and then identifying new proteins that fit the model. A further advance was the development of iterative methods that refine the model as more homologs are discovered. These methods are generally limited by ad hoc methods of sequence weighting, neglect of underlying evolutionary relationships and the representation of the set with a single one-size-fits-all model. These limitations are avoided through the use of a Tree hidden Markov model (T-HMM) approach. Our previous work described how a non-iterative version of the T-HMM method could identify distant homologs with superior performance compared with other non-iterated approaches, and described how this method was particularly appropriate for being implemented as an iterative algorithm.
Results: We describe an iterative version of the T-HMM algorithm, and evaluate its performance for the detection of distant homologs. Significant improvement over other commonly used methods is found.
Availability: The software (C++, Perl) is available from the corresponding author.
Contact: richard.goldstein{at}nimr.mrc.ac.uk
* To whom correspondence should be addressed.
Present address: Department of Biochemistry, University of Washington, WA 98195, USA.
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