Cargando…
NetBCE: An Interpretable Deep Neural Network for Accurate Prediction of Linear B-cell Epitopes
Identification of B-cell epitopes (BCEs) plays an essential role in the development of peptide vaccines and immuno-diagnostic reagents, as well as antibody design and production. In this work, we generated a large benchmark dataset comprising 124,879 experimentally supported linear epitope-containin...
Autores principales: | Xu, Haodong, Zhao, Zhongming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025766/ https://www.ncbi.nlm.nih.gov/pubmed/36526218 http://dx.doi.org/10.1016/j.gpb.2022.11.009 |
Ejemplares similares
-
DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers
por: Chen, Shengquan, et al.
Publicado: (2021) -
Deep neural networks for interpreting RNA-binding protein target preferences
por: Ghanbari, Mahsa, et al.
Publicado: (2020) -
iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction
por: Manavalan, Balachandran, et al.
Publicado: (2018) -
DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data
por: Arisdakessian, Cédric, et al.
Publicado: (2019) -
FF‐QuantSC: accurate quantification of fetal fraction by a neural network model
por: Yuan, Yuying, et al.
Publicado: (2020)