A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences

TL;DR

This paper introduces CSminer, a computational method for identifying RNA tertiary motifs, specifically coaxial helical stackings, in genomic sequences, aiding understanding of RNA structure and stability.

Contribution

The paper presents a novel algorithm, CSminer, for detecting RNA coaxial helical stackings in genomes, advancing computational RNA motif discovery.

Findings

CSminer effectively identifies RNA coaxial stackings in genomic data.

Experimental results validate the accuracy of the method.

The approach enhances understanding of RNA tertiary structure stability.

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.