Protein model accuracy estimation empowered by deep learning and inter-residue distance prediction in CASP14
Abstract The inter-residue contact prediction and deep learning showed the promise to improve the estimation of protein model accuracy (EMA) in the 13th Critical Assessment of Protein Structure Prediction (CASP13). To further leverage the improved inter-residue distance predictions to enhance EMA, d...
Guardado en:
Autores principales: | Xiao Chen, Jian Liu, Zhiye Guo, Tianqi Wu, Jie Hou, Jianlin Cheng |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/7cc61f3613084b268a5cf7d582f47d0e |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
MULTICOM2 open-source protein structure prediction system powered by deep learning and distance prediction
por: Tianqi Wu, et al.
Publicado: (2021) -
An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12
por: Chen Keasar, et al.
Publicado: (2018) -
Analyzing effect of quadruple multiple sequence alignments on deep learning based protein inter-residue distance prediction
por: Aashish Jain, et al.
Publicado: (2021) -
Correction: PRMT5 regulates cell pyroptosis by silencing CASP1 in multiple myeloma
por: Tian Xia, et al.
Publicado: (2021) -
Improved protein structure refinement guided by deep learning based accuracy estimation
por: Naozumi Hiranuma, et al.
Publicado: (2021)