Data Collection for "Implicit Solvent Approach Based on Generalised Born and Transferable Graph Neural Networks for Molecular Dynamics Simulations"

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topologies_and_starting_coordinates.tar.gz (Gzip, 85.34Kb)
training_data.tar.gz (Gzip, 4.815Gb)
example_analysis_trajectories.tar.gz (Gzip, 802.2Mb)
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Open access
ccbyncsa
Creator
Riniker, Sereinacc
Katzberger, Paul
Date
2023-02-20
Type
    Data Collection
Rights / license
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Abstract
Data collection associated with the publication "Implicit Solvent Approach Based on Generalised Born and Transferable Graph Neural Networks for Molecular Dynamics Simulations". Contains: - Topologies and starting structures for the peptides in TIP5P water - Complete training data for the ML Show more
 
Data collection is linked to the GitHub repository: https://github.com/rinikerlab/GNNImplicitSolvent
 
Permanent link
https://doi.org/10.3929/ethz-b-000599309
Contributors
Contact person: Riniker, Sereinacc
Data collector: Katzberger, Paul
Research group: Riniker, Sereinacc
Publisher
ETH Zurich
Subject
Computational chemistry
Organisational unit
09458 - Riniker, Sereina Z. / Riniker, Sereina Z.  
Funding
ETH-50 21-1 - Development of an Improved Implicit Solvation Approach Through Machine Learning from Molecular Dynamics Simulations (ETHZ)
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