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Stochastic models of sequence evolution including insertion-deletion events (2008)
| Citations: | 13 - 3 self |
BibTeX
@MISC{Miklós08stochasticmodels,
author = {István Miklós and Ádám Novák and Rahul Satija and Rune Lyngsø and Jotun Hein},
title = {Stochastic models of sequence evolution including insertion-deletion events},
year = {2008}
}
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Abstract
Abstract. Comparison of sequences that have descended from a common ancestor based on an explicit stochastic model of substitutions, insertions and deletions has risen to prominence in the last decade. Making statements about the positions of insertions-deletions (abbr. indels) is central in sequence and genome analysis and is called alignment. This statistical approach is harder conceptually and computationally, than competing approaches based on choosing an alignment according to some optimality criteria. But it has major practical advantages in terms of testing evolutionary hypotheses and parameter estimation. Basic dynamic approaches can allow the analysis of up to 4-5 sequences. MCMC techniques can bring this to about 10-15 sequences. Beyond this, different or heuristic approaches must be used. Besides the computational challenges, increasing realism in the underlying models is presently being addressed. A recent development that has been especially fruitful is combining statistical alignment with the problem of sequence annotation, making statements about the function of each nucleotide/amino acid. So far gene finding, protein secondary structure prediction and regulatory signal detection has been tackled within this framework. Much progress can be reported, but clearly major challenges remain if this approach is to be central in the analyses of large incoming sequence data sets. 1
Keyphrases
insertion-deletion event sequence evolution stochastic model parameter estimation nucleotide amino acid last decade statistical approach computational challenge basic dynamic approach 4-5 sequence protein secondary structure prediction mcmc technique explicit stochastic model heuristic approach genome analysis recent development optimality criterion major practical advantage evolutionary hypothesis sequence annotation common ancestor major challenge underlying model much progress regulatory signal detection 10-15 sequence sequence data set statistical alignment
