Effective classification of microRNA precursors using feature mining and AdaBoost algorithms.

MicroRNAs play important roles in most biological processes, including cell proliferation, tissue differentiation, and embryonic development, among others. They originate from precursor transcripts (pre-miRNAs), which contain phylogenetically conserved stem-loop structures. An important bioinformatics problem is to distinguish the pre-miRNAs from pseudo pre-miRNAs that have similar stem-loop structures.

A computational approach to finding RNA tertiary motifs in genomic sequences: a case study.

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.

Predicting coaxial helical stacking in RNA junctions.

RNA junctions are important structural elements that form when three or more helices come together in space in the tertiary structures of RNA molecules. Determining their structural configuration is important for predicting RNA 3D structure. We introduce a computational method to predict, at the secondary structure level, the coaxial helical stacking arrangement in junctions, as well as classify the junction topology.

Mining small RNA structure elements in untranslated regions of human and mouse mRNAs using structure-based alignment.

Background: UnTranslated Regions (UTRs) of mRNAs contain regulatory elements for various aspects of mRNA metabolism, such as mRNA localization, translation, and mRNA stability. Several RNA stem-loop structures in UTRs have been experimentally identified, including the histone 3' UTR stem-loop structure (HSL3) and iron response element (IRE). These stem-loop structures are conserved among mammalian orthologs, and exist in a group of genes encoding proteins involved in the same biological pathways.