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Class-Specific Prediction of ncRNAs

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RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1097))

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.

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Authors and Affiliations

  1. Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107, Leipzig, Germany

    Peter F. Stadler

  2. Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103, Leipzig, Germany

    Peter F. Stadler

  3. Fraunhofer Institute for Cell Therapy and Immunology, Perlickstraße 1, D-04103, Leipzig, Germany

    Peter F. Stadler

  4. Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090, Wien, Austria

    Peter F. Stadler

  5. Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, DK-1870, Frederiksberg C, Denmark

    Peter F. Stadler

  6. Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501, USA

    Peter F. Stadler

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  1. Peter F. Stadler
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Editors and Affiliations

  1. Center for non-coding RNA in Technology and Health, IKVH University of Copenhagen, Frederiksberg, Denmark

    Jan Gorodkin

  2. University of Washington Dept. Computer Science & Engineering, Seattle, Washington, USA

    Walter L. Ruzzo

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Stadler, P.F. (2014). Class-Specific Prediction of ncRNAs. In: Gorodkin, J., Ruzzo, W. (eds) RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods. Methods in Molecular Biology, vol 1097. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-709-9_10

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  • DOI: https://doi.org/10.1007/978-1-62703-709-9_10

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