
We present an analysis of multi-aligned eukaryotic and procaryotic small subunit rRNA sequences using a novel segmentation and clustering procedure capable of extracting subsets of sequences that share common sequence features. This procedure consists of: i) segmentation of aligned sequences using a dynamic programming procedure, and subsequent identification of likely conserved segments; ii) for each putative conserved segment, extraction of a locall homogeneous cluster using a novel polynomial procedure; and iii) intersection of clusters associated with each conserved segment. Aside from their utilit in processing large gap-filled multi-alignments, these algorithms can be applied to a broad spectrum of rRNA analysis functions such as subalignment, phylogenetic subtree extraction and construction, and organism tree-placement, and can serve as a framework to organize sequence data in an efficient and easily searchable manner. The sequence classification we obtained using the method presented here shows a remarkable consistency with the independently constructed eukaryotic phylogenetic tree.
Models, Statistical, Sequence Analysis, RNA, Genes, Fungal, Genes, Protozoan, Eukaryota, RNA, Ribosomal, RNA, Ribosomal, 18S, Animals, Cluster Analysis, Combinatorial Chemistry Techniques, Algorithms, Phylogeny
Models, Statistical, Sequence Analysis, RNA, Genes, Fungal, Genes, Protozoan, Eukaryota, RNA, Ribosomal, RNA, Ribosomal, 18S, Animals, Cluster Analysis, Combinatorial Chemistry Techniques, Algorithms, Phylogeny
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