Document Detail


A "Long Indel" model for evolutionary sequence alignment.
MedLine Citation:
PMID:  14694074     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We present a new probabilistic model of sequence evolution, allowing indels of arbitrary length, and give sequence alignment algorithms for our model. Previously implemented evolutionary models have allowed (at most) single-residue indels or have introduced artifacts such as the existence of indivisible "fragments." We compare our algorithm to these previous methods by applying it to the structural homology dataset HOMSTRAD, evaluating the accuracy of (1) alignments and (2) evolutionary time estimates. With our method, it is possible (for the first time) to integrate probabilistic sequence alignment, with reliability indicators and arbitrary gap penalties, in the same framework as phylogenetic reconstruction. Our alignment algorithm requires that we evaluate the likelihood of any specific path of mutation events in a continuous-time Markov model, with the event times integrated out. To this effect, we introduce a "trajectory likelihood" algorithm (Appendix A). We anticipate that this algorithm will be useful in more general contexts, such as Markov Chain Monte Carlo simulations.
Authors:
I Miklós; G A Lunter; I Holmes
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2003-12-23
Journal Detail:
Title:  Molecular biology and evolution     Volume:  21     ISSN:  0737-4038     ISO Abbreviation:  Mol. Biol. Evol.     Publication Date:  2004 Mar 
Date Detail:
Created Date:  2004-03-09     Completed Date:  2005-01-07     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  8501455     Medline TA:  Mol Biol Evol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  529-40     Citation Subset:  IM    
Affiliation:
Department of Statistics, University of Oxford, Oxford, UK. miklos@stats.ox.ac.uk
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Evolution, Molecular*
Likelihood Functions
Markov Chains
Sequence Alignment / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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