A local structural prediction algorithm for RNA triple helix structure

Bay Yuan Hsu, Thomas K.F. Wong, Wing Kai Hon, Xinyi Liu, Tak Wah Lam, Siu Ming Yiu*

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    Secondary structure prediction (with or without pseudoknots) of an RNA molecule is a well-known problem in computational biology. Most of the existing algorithms have an assumption that each nucleotide can interact with at most one other nucleotide. This assumption is not valid for triple helix structure (a pseudoknotted structure with tertiary interactions). As these structures are found to be important in many biological processes, it is desirable to develop a prediction tool for these structures. We provide the first structural prediction algorithm to handle triple helix structures. Our algorithm runs in O(n 3) time where n is the length of input RNA sequence. The accuracy of the prediction is reasonably high, with average sensitivity and specificity over 80% for base pairs, and over 70% for tertiary interactions.

    Original languageEnglish
    Title of host publicationPattern Recognition in Bioinformatics - 8th IAPR International Conference, PRIB 2013, Proceedings
    PublisherSpringer Verlag
    Pages102-113
    Number of pages12
    ISBN (Print)9783642391583
    DOIs
    Publication statusPublished - 2013
    Event8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013 - Nice, France
    Duration: 17 Jun 201320 Jun 2013

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume7986 LNBI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013
    Country/TerritoryFrance
    CityNice
    Period17/06/1320/06/13

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