@inproceedings{5bbcfef8ebe143069a487fcf695fa238,
title = "An efficient method for validating protein models using electron microscopy data",
abstract = "Cryo-Electron Microscopy is a powerful biophysical technique that is capable of generating 3-dimensional volume images for macromolecular assemblies and machines. De novo protein modeling uses these images to model the biological molecules. In de novo modeling, many candidate structures are generated at intermediate step. The candidates are evaluated conventionally by time-consuming approaches. We introduce an initial version of a geometrical screening method that uses the skeleton of the cryo-EM images to evaluate the candidate structures. A test of ten (10) proteins shows that our method was able to successfully detect good candidates in an efficient way.",
keywords = "Cryo-EM, De novo modeling, Geometrical screening, Protein modeling, Skeleton",
author = "{Al Nasr}, Kamal and Christopher Jones and Bashar Aboona and Abdulrahman Alanazi",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 ; Conference date: 15-12-2016 Through 18-12-2016",
year = "2017",
month = jan,
day = "17",
doi = "10.1109/BIBM.2016.7822778",
language = "English (US)",
series = "Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1726--1731",
editor = "Kevin Burrage and Qian Zhu and Yunlong Liu and Tianhai Tian and Yadong Wang and Hu, {Xiaohua Tony} and Qinghua Jiang and Jiangning Song and Shinichi Morishita and Kevin Burrage and Guohua Wang",
booktitle = "Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016",
}