A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences: A Case Study
Kevin Byron, Christian Laing, Dongrong Wen and Jason T.L. Wang
Affiliation: Bioinformatics Program and Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey 07102, USA.
Motif finding in DNA, RNA and proteins plays an important role in life science research. Recent patents concerning
motif finding in biomolecular data are recorded in the DNA Patent Database which serves as a resource for policy
makers and members of the general public interested in fields like genomics, genetics and biotechnology. In this paper, we
present a computational approach to mining for RNA tertiary motifs in genomic sequences. Specifically, we describe a
method, named CSminer, and show, as a case study, the application of CSminer to genome-wide search for coaxial helical
stackings in RNA 3-way junctions. A coaxial helical stacking occurs in an RNA 3-way junction where two separate helical
elements form a pseudocontiguous helix and provide thermodynamic stability to the RNA molecule as a whole. Experimental
results demonstrate the effectiveness of our approach.
Keywords: Coaxial helical stacking, genome-wide motif finding, RNA junction.
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