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.
Guardado en:
Autores principales: | Jaswinder Singh, Jack Hanson, Kuldip Paliwal, Yaoqi Zhou |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/90cc291b0b6b40a7a04fcac4f370cd90 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Deep Convolutional Neural Network Ensembles Using ECOC
por: Sara Atito Ali Ahmed, et al.
Publicado: (2021) -
Ensemble Models of Cutting-Edge Deep Neural Networks for Blood Glucose Prediction in Patients with Diabetes
por: Félix Tena, et al.
Publicado: (2021) -
RNA secondary structure prediction using deep learning with thermodynamic integration
por: Kengo Sato, et al.
Publicado: (2021) -
Integrating ensemble systems biology feature selection and bimodal deep neural network for breast cancer prognosis prediction
por: Li-Hsin Cheng, et al.
Publicado: (2021) -
DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra
por: Da-Wei Li, et al.
Publicado: (2021)