Cargando…
Recent developments in deep learning applied to protein structure prediction
Although many structural bioinformatics tools have been using neural network models for a long time, deep neural network (DNN) models have attracted considerable interest in recent years. Methods employing DNNs have had a significant impact in recent CASP experiments, notably in CASP12 and especiall...
Autores principales: | Kandathil, Shaun M., Greener, Joe G., Jones, David T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6899861/ https://www.ncbi.nlm.nih.gov/pubmed/31589782 http://dx.doi.org/10.1002/prot.25824 |
Ejemplares similares
-
Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13
por: Hou, Jie, et al.
Publicado: (2019) -
Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)
por: Senior, Andrew W., et al.
Publicado: (2019) -
Evaluation of template‐based modeling in CASP13
por: Croll, Tristan I., et al.
Publicado: (2019) -
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
por: Greener, Joe G., et al.
Publicado: (2019) -
Prediction of interresidue contacts with DeepMetaPSICOV in CASP13
por: Kandathil, Shaun M., et al.
Publicado: (2019)