Computational identification of evolutionarily conserved exons

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Computational identification of evolutionarily conserved exons
Phylogenetic hidden Markov models (phylo-HMMs) have recently been proposed as a means for addressing a multispecies version of the ab initio gene prediction problem. These models allow sequence divergence, a phylogeny, patterns of substitution, and base composition all to be considered simultaneously, in a single unified probabilistic model. Here, we apply phylo-HMMs to a restricted version of the gene prediction problem in which individual exons are sought that are evolutionarily conserved across a diverse set of species. We discuss two new methods for improving prediction performance: (1) the use of context-dependent phylogenetic models, which capture phenomena such as a strong CpG effect in noncoding regions and a preference for synonymous rather than nonsynonymous substitutions in coding regions; and (2) a novel strategy for incorporating insertions and deletion (indels) into the state-transition structure of the model, which captures the different characteristic patterns of align...
Adam C. Siepel, David Haussler
Added 03 Dec 2009
Updated 03 Dec 2009
Type Conference
Year 2004
Authors Adam C. Siepel, David Haussler
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