Cargando…
Improving Protein Fold Recognition by Deep Learning Networks
For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evalua...
Autores principales: | Jo, Taeho, Hou, Jie, Eickholt, Jesse, Cheng, Jianlin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4669437/ https://www.ncbi.nlm.nih.gov/pubmed/26634993 http://dx.doi.org/10.1038/srep17573 |
Ejemplares similares
-
Improving protein fold recognition by random forest
por: Jo, Taeho, et al.
Publicado: (2014) -
DNdisorder: predicting protein disorder using boosting and deep networks
por: Eickholt, Jesse, et al.
Publicado: (2013) -
A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks
por: Eickholt, Jesse, et al.
Publicado: (2013) -
DeepSF: deep convolutional neural network for mapping protein sequences to folds
por: Hou, Jie, et al.
Publicado: (2018) -
NNcon: improved protein contact map prediction using 2D-recursive neural networks
por: Tegge, Allison N., et al.
Publicado: (2009)