A generalized deep learning approach for local structure identification in molecular simulations
Abstract
We demonstrate a PointNet-based deep learning approach to classify local structure in molecular simulations, learning features directly from atomic coordinates.
- Authors:
-
[1];
[2];
[1]
- Department of Chemical & Biomolecular Engineering, Clemson University, Clemson, USA
- Department of Electrical & Computer Engineering, Clemson University, Clemson, USA
- Publication Date:
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
- OSTI Identifier:
- 1542673
- Grant/Contract Number:
- SC0015448
- Resource Type:
- Published Article
- Journal Name:
- Chemical Science
- Additional Journal Information:
- Journal Name: Chemical Science Journal Volume: 10 Journal Issue: 32; Journal ID: ISSN 2041-6520
- Publisher:
- Royal Society of Chemistry (RSC)
- Country of Publication:
- United Kingdom
- Language:
- English
Citation Formats
DeFever, Ryan S., Targonski, Colin, Hall, Steven W., Smith, Melissa C., and Sarupria, Sapna. A generalized deep learning approach for local structure identification in molecular simulations. United Kingdom: N. p., 2019.
Web. doi:10.1039/C9SC02097G.
DeFever, Ryan S., Targonski, Colin, Hall, Steven W., Smith, Melissa C., & Sarupria, Sapna. A generalized deep learning approach for local structure identification in molecular simulations. United Kingdom. doi:10.1039/C9SC02097G.
DeFever, Ryan S., Targonski, Colin, Hall, Steven W., Smith, Melissa C., and Sarupria, Sapna. Wed .
"A generalized deep learning approach for local structure identification in molecular simulations". United Kingdom. doi:10.1039/C9SC02097G.
@article{osti_1542673,
title = {A generalized deep learning approach for local structure identification in molecular simulations},
author = {DeFever, Ryan S. and Targonski, Colin and Hall, Steven W. and Smith, Melissa C. and Sarupria, Sapna},
abstractNote = {We demonstrate a PointNet-based deep learning approach to classify local structure in molecular simulations, learning features directly from atomic coordinates.},
doi = {10.1039/C9SC02097G},
journal = {Chemical Science},
number = 32,
volume = 10,
place = {United Kingdom},
year = {2019},
month = {8}
}
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1039/C9SC02097G
DOI: 10.1039/C9SC02097G
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Works referenced in this record:
Molecular dynamics study of melting and freezing of small Lennard-Jones clusters
journal, September 1987
- Honeycutt, J. Dana.; Andersen, Hans C.
- The Journal of Physical Chemistry, Vol. 91, Issue 19, p. 4950-4963
A simple method for displaying the hydropathic character of a protein
journal, May 1982
- Kyte, Jack; Doolittle, Russell F.
- Journal of Molecular Biology, Vol. 157, Issue 1, p. 105-132