A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences
Abstract
Motif finding in DNA, RNA and proteins plays an important role in life science research. Recent patents concerning motif finding in the 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, for finding RNA coaxial helical stackings in genomes. A coaxial helical stacking occurs in an RNA tertiary structure where two separate helical elements form a pseudocontiguous helix and provides thermodynamic stability to the molecule as a whole. Experimental results demonstrate the effectiveness of our approach.
Cite
@article{arxiv.1701.00435,
title = {A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences},
author = {Kevin Byron and Jason T. L. Wang},
journal= {arXiv preprint arXiv:1701.00435},
year = {2017}
}
Comments
23 pages, 9 figures, 3 tables