RAG: RNA-As-Graphs database---concepts, analysis, and features

  • Authors:

  • Hin Hark Gan;Daniela Fera;Julie Zorn;Nahum Shiffeldrim;Michael Tang;Uri Laserson;Namhee Kim;Tamar Schlick

  • Affiliations:

  • Department of Chemistry, New York University, New York, NY 10003, USA,;Department of Chemistry, New York University, New York, NY 10003, USA,;Department of Chemistry, New York University, New York, NY 10003, USA,;Department of Chemistry, New York University, New York, NY 10003, USA,;Department of Chemistry, New York University, New York, NY 10003, USA,;Department of Chemistry, New York University, New York, NY 10003, USA,;Department of Chemistry, New York University, New York, NY 10003, USA,;Department of Chemistry, New York University, New York, NY 10003, USA,

  • Venue:
  • Bioinformatics
  • Year:
  • 2004

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Abstract

Motivation: Understanding RNA's structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNA's structural repertoire. Results: Our RNA-As-Graphs (RAG) database describes and ranks all mathematically possible (including existing and candidate) RNA secondary motifs on the basis of graphical enumeration techniques. We represent RNA secondary structures as two-dimensional graphs (networks), specifying the connectivity between RNA secondary structural elements, such as loops, bulges, stems and junctions. We archive RNA tree motifs as 'tree graphs' and other RNAs, including pseudoknots, as general 'dual graphs'. All RNA motifs are catalogued by graph vertex number (a measure of sequence length) and ranked by topological complexity. The RAG inventory immediately suggests candidates for novel RNA motifs, either naturally occurring or synthetic, and thereby might stimulate the prediction and design of novel RNA motifs. Availability: The database is accessible on the web at http://monod.biomath.nyu.edu/rna