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dc.contributor.authorHuang, HDen_US
dc.contributor.authorHorng, JTen_US
dc.contributor.authorWu, LCen_US
dc.contributor.authorFang, SFen_US
dc.date.accessioned2014-12-08T15:18:43Z-
dc.date.available2014-12-08T15:18:43Z-
dc.date.issued2005-08-01en_US
dc.identifier.issn0218-2130en_US
dc.identifier.urihttp://dx.doi.org/10.1142/S0218213005002296en_US
dc.identifier.urihttp://hdl.handle.net/11536/13466-
dc.description.abstractCertain structural motifs, like tetra-loops, in ribosomal RNA are known to functionally implicate in virtually every aspect of protein synthesis. Ribosomal RNA molecules were also widely used as a tool in molecular evolutionary studies because of their ubiquity, size and low evolutionary rate. In this study, we adapt a data mining approach to discover common structural motifs, and then we use a machine learning approach to identify discriminating CSMs from groups of organisms. Finally, we construct phylogeneitc trees to investigate the evolution of ribosomal RNA by serving the CSMs discovered as targets, which are used to estimate the evolutionary relatedness between organisms. The aim of this study is to discover common structural motifs (CSMs), i.e., those single-strain regions shared in ribosomal RNA secondary structures by several organisms, which are related to specific domains or functions. We discover a set of common structural motifs from several data sets of Archaea and Bacteria. Significant CSMs are then induced by a decision tree. Furthermore, phylogenetic trees are constructed based on CSMs and primary sequences of SSU 16 S ribosomal RNA.en_US
dc.language.isoen_USen_US
dc.subjectSSU 16 rRNAen_US
dc.subjectmotifsen_US
dc.subjectdata miningen_US
dc.titleDiscovering common structural motifs of ribosomal RNA secondary structures in prokaryotesen_US
dc.typeArticleen_US
dc.identifier.doi10.1142/S0218213005002296en_US
dc.identifier.journalINTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLSen_US
dc.citation.volume14en_US
dc.citation.issue4en_US
dc.citation.spage621en_US
dc.citation.epage639en_US
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000233469200005-
dc.citation.woscount1-
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