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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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| 出版年: | Nat Commun |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Nature Publishing Group UK
2021
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| 主題: | |
| オンライン･アクセス: | 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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