Rapid prediction of protein natural frequencies using graph neural networks

Author(s)
Guo, Kai; Buehler, Markus J
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Creative Commons Attribution NonCommercial License 3.0 https://creativecommons.org/licenses/by-nc/3.0/
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Abstract
<jats:p>We present a computational framework based on graph neural networks (GNNs) to predict the natural frequencies of proteins from primary amino acid sequences and contact/distance maps.</jats:p>
Date issued
2022
URI
https://hdl.handle.net/1721.1/146553
Department
Massachusetts Institute of Technology. Laboratory for Atomistic and Molecular Mechanics; Massachusetts Institute of Technology. Center for Computational Science and Engineering; Massachusetts Institute of Technology. Center for Materials Science and Engineering
Journal
Digital Discovery
Publisher
Royal Society of Chemistry (RSC)
Citation
Guo, Kai and Buehler, Markus J. 2022. "Rapid prediction of protein natural frequencies using graph neural networks." Digital Discovery, 1 (3).
Version: Final published version
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