An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors.
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%0 Journal Article
%1 journals/jcisd/LiLCYYGGP22
%A Li, Chuan
%A Liu, Jiangting
%A Chen, Jianfang
%A Yuan, Yuan
%A Yu, Jin
%A Gou, Qiaolin
%A Guo, Yanzhi
%A Pu, Xuemei
%D 2022
%J J. Chem. Inf. Model.
%K dblp
%N 6
%P 1399-1410
%T An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors.
%U http://dblp.uni-trier.de/db/journals/jcisd/jcisd62.html#LiLCYYGGP22
%V 62
@article{journals/jcisd/LiLCYYGGP22,
added-at = {2022-05-18T00:00:00.000+0200},
author = {Li, Chuan and Liu, Jiangting and Chen, Jianfang and Yuan, Yuan and Yu, Jin and Gou, Qiaolin and Guo, Yanzhi and Pu, Xuemei},
biburl = {https://www.bibsonomy.org/bibtex/251aa6eb018f38e01d307184d538a075c/dblp},
ee = {https://doi.org/10.1021/acs.jcim.2c00085},
interhash = {e266660b5aa1a9d386d75e7616b52a10},
intrahash = {51aa6eb018f38e01d307184d538a075c},
journal = {J. Chem. Inf. Model.},
keywords = {dblp},
number = 6,
pages = {1399-1410},
timestamp = {2024-04-08T17:30:05.000+0200},
title = {An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors.},
url = {http://dblp.uni-trier.de/db/journals/jcisd/jcisd62.html#LiLCYYGGP22},
volume = 62,
year = 2022
}
