RNA secondary structure prediction from multi-aligned sequences

    Research output: Chapter in Book/Report/Conference proceedingChapter

    1 Citation (Scopus)

    Abstract

    It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.

    Original languageEnglish
    Title of host publicationRNA Bioinformatics
    PublisherSpringer New York
    Pages17-38
    Number of pages22
    ISBN (Print)9781493922918, 9781493922901
    DOIs
    Publication statusPublished - 2015 Jan 10

    Keywords

    • Common/consensus secondary structures
    • Comparative methods
    • Covariation
    • Energy model
    • Maximum expected gain (MEG) estimators
    • Multiple sequence alignment
    • Mutual information
    • Phylogenetic tree
    • Probabilistic model

    ASJC Scopus subject areas

    • Medicine(all)
    • Biochemistry, Genetics and Molecular Biology(all)

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