RNA secondary structure prediction by conducting multi-class classifications

Generating valid predictions of RNA secondary structures is challenging. Several deep learning methods have been developed for predicting RNA secondary structures. However, they commonly adopt post-processing steps to adjust the model output to produce valid predictions, which are complicated and co...

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Bibliographic Details
Main Authors: Jiyuan Yang, Kengo Sato, Martin Loza, Sung-Joon Park, Kenta Nakai
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037025001229
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