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
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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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