title: Class-specific prediction of ncRNAs.
abstract: Many RNA families, i.e., groups of homologous RNA genes, belong to RNA classes, such as tRNAs, snoRNAs, or microRNAs, that are characterized by common sequence motifs and/or common secondary structure features. The detection of new members of RNA classes, as well as the comprehensive annotation of genomes with members of RNA classes is a challenging task that goes beyond simple homology search. Computational methods addressing this problem typically use a three-tiered approach: In the first step an efficient and sensitive filter is employed. In the second step the candidate set is narrowed down using computationally expensive methods geared towards specificity. In the final step the hits are annotated with class-specific features and scored. Here we review the tools that are currently available for a diverse set of RNA classes.
authors.affiliation: Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107, Leipzig, Germany.
authors.forename: Peter F
authors.initials: PF
authors.lastname: Stadler
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D020407:Internet; D009690:Nucleic Acid Conformation; D022661:RNA, Untranslated / Q000737:chemistry* / Q000145:classification; D016415:Sequence Alignment / Q000379:methods; D017423:Sequence Analysis, RNA / Q000379:methods; D012984:Software
chemical_list: D022661:RNA, Untranslated