Cargando…
P3CMQA: Single-Model Quality Assessment Using 3DCNN with Profile-Based Features
Model quality assessment (MQA), which selects near-native structures from structure models, is an important process in protein tertiary structure prediction. The three-dimensional convolution neural network (3DCNN) was applied to the task, but the performance was comparable to existing methods becau...
Autores principales: | Takei, Yuma, Ishida, Takashi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003382/ https://www.ncbi.nlm.nih.gov/pubmed/33808604 http://dx.doi.org/10.3390/bioengineering8030040 |
Ejemplares similares
-
A Benchmark Dataset for Evaluating Practical Performance of Model Quality Assessment of Homology Models
por: Takei, Yuma, et al.
Publicado: (2022) -
Surgical workflow recognition with 3DCNN for Sleeve Gastrectomy
por: Zhang, Bokai, et al.
Publicado: (2021) -
BEMD-3DCNN-based method for COVID-19 detection
por: Riahi, Ali, et al.
Publicado: (2022) -
RNA3DCNN: Local and global quality assessments of RNA 3D structures using 3D deep convolutional neural networks
por: Li, Jun, et al.
Publicado: (2018) -
A 3DCNN-Based Knowledge Distillation Framework for Human Activity Recognition
por: Ullah, Hayat, et al.
Publicado: (2023)