Computational approaches for predicting mutation effects on RNA Sstructure

    Abstract

    Noncoding RNA (ncRNA) is now well characterized for its role in various cellular functions, including housekeeping and regulation. The structural characteristics of many ncRNAs are essential for their function. Traditional mutagenesis experiments help to study the structure-function relationship of ribonucleic acids (RNAs) by introducing artificial (random or site-directed) mutations that stabilize/destabilize the RNA structure. Furthermore, naturally occurring variants (such as single nucleotide polymorphisms or mutations) on RNA may also disrupt the RNA structure-function relationship and can sometimes be associated with diseases or traits. The secondary structure of an RNA sequence can be predicted in various ways by many different RNA folding methods. Here, we review the current computational methods, based on the RNA folding algorithms, for predicting mutation effects on RNA secondary structure.

    OriginalsprogEngelsk
    TitelBioinformatics
    RedaktørerBengt Persson
    Antal sider11
    ForlagElsevier
    Publikationsdato25 jul. 2014
    Sider111-121
    Kapitel6.08
    ISBN (Trykt)978-0-444-53632-7
    DOI
    StatusUdgivet - 25 jul. 2014
    NavnComprehensive biomedical physics
    Vol/bind6

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