Computer Science – Learning
Scientific paper
2009-06-15
Comparative Genomics, International Workshop (RECOMB-CG), 5817 volume of Lecture Notes in Bioinformatics, pp. 150-163, Budapes
Computer Science
Learning
Scientific paper
10.1007/978-3-642-04744-2_13
Clusters of genes that have evolved by repeated segmental duplication present difficult challenges throughout genomic analysis, from sequence assembly to functional analysis. Improved understanding of these clusters is of utmost importance, since they have been shown to be the source of evolutionary innovation, and have been linked to multiple diseases, including HIV and a variety of cancers. Previously, Zhang et al. (2008) developed an algorithm for reconstructing parsimonious evolutionary histories of such gene clusters, using only human genomic sequence data. In this paper, we propose a probabilistic model for the evolution of gene clusters on a phylogeny, and an MCMC algorithm for reconstruction of duplication histories from genomic sequences in multiple species. Several projects are underway to obtain high quality BAC-based assemblies of duplicated clusters in multiple species, and we anticipate that our method will be useful in analyzing these valuable new data sets.
Brejová Broňa
Siepel Adam
Song Giltae
Vinař Tomáš
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