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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...
Autores principales: | Sato, Kengo, Akiyama, Manato, Sakakibara, Yasubumi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7878809/ https://www.ncbi.nlm.nih.gov/pubmed/33574226 http://dx.doi.org/10.1038/s41467-021-21194-4 |
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