Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data

Bioinformatics. 2006 Jul 15;22(14):e197-202. doi: 10.1093/bioinformatics/btl257.

Abstract

Recently, genome-wide surveys for non-coding RNAs have provided evidence for tens of thousands of previously undescribed evolutionary conserved RNAs with distinctive secondary structures. The annotation of these putative ncRNAs, however, remains a difficult problem. Here we describe an SVM-based approach that, in conjunction with a non-stringent filter for consensus secondary structures, is capable of efficiently recognizing microRNA precursors in multiple sequence alignments. The software was applied to recent genome-wide RNAz surveys of mammals, urochordates, and nematodes.

Availability: The program RNAmicro is available as source code and can be downloaded from http://www.bioinf.uni-leipzig/Software/RNAmicro.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Artificial Intelligence
  • Base Sequence
  • Chromosome Mapping / methods*
  • Conserved Sequence
  • Databases, Genetic*
  • Genomics / methods
  • Humans
  • Information Storage and Retrieval / methods
  • MicroRNAs / chemistry*
  • MicroRNAs / genetics
  • Molecular Sequence Data
  • Pattern Recognition, Automated / methods
  • RNA Precursors / chemistry*
  • RNA Precursors / genetics
  • Sequence Alignment / methods*
  • Sequence Analysis, RNA / methods*
  • Sequence Homology, Nucleic Acid
  • Software

Substances

  • MicroRNAs
  • RNA Precursors