RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning

The limited availability of high-resolution 3D RNA structures for model training limits RNA secondary structure prediction. Here, the authors overcome this challenge by pre-training a DNN on a large set of predicted RNA structures and using transfer learning with high-resolution structures.

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Auteurs principaux: Jaswinder Singh, Jack Hanson, Kuldip Paliwal, Yaoqi Zhou
Format: article
Langue:EN
Publié: Nature Portfolio 2019
Sujets:
Q
Accès en ligne:https://doaj.org/article/90cc291b0b6b40a7a04fcac4f370cd90
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