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When will RNA get its AlphaFold moment?

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652036%3A_____%2F23%3A00582988" target="_blank" >RIV/86652036:_____/23:00582988 - isvavai.cz</a>

  • Result on the web

    <a href="https://academic.oup.com/nar/article/51/18/9522/7272628?login=true" target="_blank" >https://academic.oup.com/nar/article/51/18/9522/7272628?login=true</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1093/nar/gkad726" target="_blank" >10.1093/nar/gkad726</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    When will RNA get its AlphaFold moment?

  • Original language description

    The protein structure prediction problem has been solved for many types of proteins by AlphaFold. Recently, there has been considerable excitement to build off the success of AlphaFold and predict the 3D structures of RNAs. RNA prediction methods use a variety of techniques, from physics-based to machine learning approaches. We believe that there are challenges preventing the successful development of deep learning-based methods like AlphaFold for RNA in the short term. Broadly speaking, the challenges are the limited number of structures and alignments making data-hungry deep learning methods unlikely to succeed. Additionally, there are several issues with the existing structure and sequence data, as they are often of insufficient quality, highly biased and missing key information. Here, we discuss these challenges in detail and suggest some steps to remedy the situation. We believe that it is possible to create an accurate RNA structure prediction method, but it will require solving several data quality and volume issues, usage of data beyond simple sequence alignments, or the development of new less data-hungry machine learning methods.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10608 - Biochemistry and molecular biology

Result continuities

  • Project

    <a href="/en/project/LM2023055" target="_blank" >LM2023055: Czech National Infrastructure for Biological Data</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Nucleic Acids Research

  • ISSN

    0305-1048

  • e-ISSN

    1362-4962

  • Volume of the periodical

    51

  • Issue of the periodical within the volume

    18

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    11

  • Pages from-to

    9522-9352

  • UT code for WoS article

    001064570800001

  • EID of the result in the Scopus database

    2-s2.0-85175135995