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Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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https://doi.org/10.5281/zenodo...
Dataset . 2021
License: CC BY
Data sources: Sygma
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Research data supporting: "A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields"

Authors: Capelli, Riccardo; Gardin, Andrea; Empereur-mot, Charly; Doni, Giovanni; Pavan, Giovanni Maria;

Research data supporting: "A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields"

Abstract

This repository contains the data used in the paper of Capelli et al. "A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields", published on Journal of Physical Chemistry B (DOI: 0.1021/acs.jpcb.1c02503). The archive traj_processed.tar.gz contains the trajectories converted in xyz format with the dimensions of the box. The archive trajectories_xtc.tar.gz contains the raw trajectories (of the membranes without solvent) in gromacs xtc format with a .tpr binary file.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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