Rapid prediction of protein natural frequencies using graph neural networks
Name
d1dd00007a.pdf
Description
Published version
Size
1.01 MB
Format
Adobe PDF
Checksum (MD5)
ebf4745ac9d16d227e537c2390695921
Author(s)
Guo, Kai
Buehler, Markus J
Date Issued
2022
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
Abstract
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.
MIT 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
Terms of Use
Creative Commons Attribution NonCommercial License 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1039/D1DD00007A
