Dataset

Data for: ART-SM: Boosting Fragment-Based Backmapping by Machine Learning

The simulation files, molecule topologies, and analysis workflows required to generate the results of our paper 'ART-SM: Boosting Fragment-Based Backmapping by Machine Learning' published in J. Chem. Theory Comput..

In details:

simulations.tar.gz: Contains the pdb (molecular structure), xtc (trajectory), mdp (MD parameters), itp (topology), and top (topology) files. GROMACS 2021 or 2023 was used for the simulations (see paper for details). Additionally, ART-SM mapping files (generated with version 1.0) and Backward mapping files from coarse-grained to atomistic resolution are included. workflows.tar.gz: Snakemake was used to handle the analysis workflows. The corresponding Snakefiles and python/bash scripts to reproduce the results in the paper are included. The actual results are not included (see paper instead). The main packages required for reproducing the results are listed under 'Software Metadata - Software Requirements'. If a second version is specified it was used only for 'sds_capb_section_4_4'. The first specified version was used for all other analyses.

Please have a look at the README files contained in each .tar.gz file.

Chemical Info

Data and Resources

Metadata Information

Field Value
DOI https://doi.org/10.18419/DARUS-4134
License URL
Source https://doi.org/10.18419/DARUS-4134
Version
Author Pluhackova, Kristyna, Pfaendner, Christian, Unger, Benjamin, Korn, Viktoria Helena
Maintainer DaRUS
Language English
MetadataPublished
Related Molecule
Field Value
No additional information available for this Dataset.
Data-Source Molecule ID Data-Source
The data in this table is sourced from UniChem at EBI.