Predicting RNA:DNA Triplex Structures from Sequence Features Using Deep Learning Architectures
The paper develops deep learning models to predict RNA:DNA triplex formation potential in lncRNAs and DNA sites using sequence features.
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Moscow Institute of Physics and TechnologyORCID 0000-0002-1526-1305Unclaimed ORCID profile · follow to get notified of new preprints
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The paper develops deep learning models to predict RNA:DNA triplex formation potential in lncRNAs and DNA sites using sequence features.
This study develops four deep learning models to predict RNA:DNA triplex formation potential using histone modification features, identifying novel lncRNAs and DNA sites.
Manoj S. Kambara, Onyinye Chukka, K. Choi…·Leonardo Mariño‐Ramírez
This paper uses explainable machine learning to identify and quantify T2D risk factors contributing to health disparities among different racial and ethnic groups in the All of Us research program.