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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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/90cc291b0b6b40a7a04fcac4f370cd90 |
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| Sumario: | 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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