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RNA secondary structure prediction using deep learning with thermodynamic integration

Accurate predictions of RNA secondary structures can help uncover the roles of functional non-coding RNAs. Although machine learning-based models have achieved high performance in terms of prediction accuracy, overfitting is a common risk for such highly parameterized models. Here we show that overf...

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Dades bibliogràfiques
Publicat a:Nat Commun
Autors principals: Sato, Kengo, Akiyama, Manato, Sakakibara, Yasubumi
Format: Artigo
Idioma:Inglês
Publicat: Nature Publishing Group UK 2021
Matèries:
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC7878809/
https://ncbi.nlm.nih.gov/pubmed/33574226
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-021-21194-4
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