{"title":"Large language modeling and deep learning shed light on RNA structure prediction","authors":"","doi":"10.1038/s41592-024-02488-z","DOIUrl":null,"url":null,"abstract":"We present an RNA language model-based deep learning pipeline for accurate and rapid de novo RNA 3D structure prediction, demonstrating strong accuracy in modeling single-stranded RNAs and excellent generalization across RNA families and types while also being capable of capturing local features such as interhelical angles and secondary structures.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"21 12","pages":"2237-2238"},"PeriodicalIF":32.1000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Methods","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41592-024-02488-z","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
We present an RNA language model-based deep learning pipeline for accurate and rapid de novo RNA 3D structure prediction, demonstrating strong accuracy in modeling single-stranded RNAs and excellent generalization across RNA families and types while also being capable of capturing local features such as interhelical angles and secondary structures.
期刊介绍：
Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.
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