Discovering common structural motifs of ribosomal RNA secondary structures in prokaryotes

Hsien Da Huang, Jorng Tzong Horng, Li Cheng Wu, Shu Fen Fang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Certain 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.

Original languageEnglish
Pages (from-to)621-639
Number of pages19
JournalInternational Journal on Artificial Intelligence Tools
Issue number4
StatePublished - Aug 2005


  • Data mining
  • Motifs
  • SSU 16 rRNA


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