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Evolutionary Structure Conservation and Covariance Scores

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RNA Folding

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2726))

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Abstract

Effective homology search for non-coding RNAs is frequently not possible via sequence similarity alone. Current methods leverage evolutionary information like structure conservation or covariance scores to identify homologs in organisms that are phylogenetically more distant. In this chapter, we introduce the theoretical background of evolutionary structure conservation and covariance score, and we show hands-on how current methods in the field are applied on example datasets.

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Author information

Authors and Affiliations

  1. Bioinformatics Group, Department of Computer Science University of Freiburg, Freiburg, Germany

    Florian Eggenhofer

  2. Bioinformatics Group, Department of Computer Science, University of Leipzig, Leipzig, Germany

    Christian Höner zu Siederdissen

  3. Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany

    Christian Höner zu Siederdissen

  4. Bioinformatics/High-Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Jena, Germany

    Christian Höner zu Siederdissen

Authors
  1. Florian Eggenhofer
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  2. Christian Höner zu Siederdissen
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Corresponding author

Correspondence to Christian Höner zu Siederdissen .

Editor information

Editors and Affiliations

  1. Institute for Theoretical Chemistry, University of Vienna, Wien, Wien, Austria

    Ronny Lorenz

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© 2024 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Eggenhofer, F., Höner zu Siederdissen, C. (2024). Evolutionary Structure Conservation and Covariance Scores. In: Lorenz, R. (eds) RNA Folding. Methods in Molecular Biology, vol 2726. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3519-3_11

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  • DOI: https://doi.org/10.1007/978-1-0716-3519-3_11

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3518-6

  • Online ISBN: 978-1-0716-3519-3

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