RNAMAT: An efficient method to detect classes of RNA molecules and their structural features

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4 Scopus citations

Abstract

There is a growing appreciation for the diverse and important roles RNA molecules play in cellular function. RNAMAT is an approach based on matrix representation of all potential base-pairing of a set of sequences to reveal common secondary-structure features. When the RNA sequences come from one class, proper summation of these matrices exposes common structural features as demonstrated for tRNA and HACA-RNA. For C/D-RNA, a novel structural motif is suggested. Furthermore, it is demonstrated, in the case of tmRNA that the method can detect pseudo-knots which are structural motifs that are difficult to detect in other methods. When the sequences come from diverse sources, a specific clustering algorithm is suggested that is capable of detecting the common motifs. The algorithm is demonstrated in a case of a simulated example and in a real case derived from Trypanosomes comparative RNomics study.

Original languageEnglish
Pages (from-to)2869-2872
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 IV
StatePublished - 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: 1 Sep 20045 Sep 2004

Keywords

  • Clustering
  • Dotplot
  • Pseudo-knots
  • RNA folding

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