Data · dataset · 2025
Data for: ART-SM: Boosting Fragment-Based Backmapping by Machine Learning
Listed in DaRUS
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.
Description
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.
Read the rest (2 more)
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.
Links
Where it is published
- Dataverse dataset page darus.uni-stuttgart.de/dataset.xhtml?persistentId=doi%3A10.18419%2FDARUS-4134 ↗
landing page · from darus uni stuttgart de
- DOI doi.org/10.18419/darus-4134 ↗
DOI / persistent id · from darus uni stuttgart de
Catalogue records · 1
- Dataverse API darus.uni-stuttgart.de/api/datasets/:persistentId/?persistentId=doi%3A10.18419%2FDARU… ↗
metadata API · from darus uni stuttgart de
Topics
- From keywords
- Artificial intelligence · Chemistry · Computer Science & AI · Life Sciences · Physics
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DaRUS | doi:10.18419/DARUS-4134 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4602 | mapping · darus uni stuttgart de | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].dataverse_subject:chemistry | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:physics | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:physics | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[method].local:method:simulation | enrichment · darus uni stuttgart de | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| description | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /description |
| publication_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| title | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /name |
| updated_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| version_label | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 |