Self Organising Maps for the Analysis of Molecular Dynamics Data
Overview
Processes data from Molecular Dynamics simulations using Self Organising Maps. Features include the ability to read different input formats. Trajectories can be analysed to identify groups of important frames. Output visualisation can be generated for maps and pathways. Methodological details can be found in Motta S et al (2022) doi:10.1021/acs.jctc.1c01163. I/O functions for xtc format files were implemented using the 'xdrfile' library available under open source license. The relevant information can be found in inst/COPYRIGHT.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 36
- Examples that run
- 96%25 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 96%
- Documented parameters
- 99%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing SOMMD adds 13 packages (9 with compiled code, 13 MB of source tarballs). Heaviest: igraph 4.8 MB, Rcpp 1.8 MB, bio3d 1.5 MB.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 0.1.2Latest2024-10-02 · current release
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2024-10-02
- Total releases
- 1 / 2 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 746 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("SOMMD")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1021/acs.jctc.1c01163.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.