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http://bura.brunel.ac.uk/handle/2438/31279| Title: | SOMMD: An R Package for the Analysis of Molecular Dynamics Simulations using Self-Organising Map |
| Authors: | Motta, S Callea, L Ismail Mulla, S Davoudkhani, H Bonati, L Pandini, A |
| Issue Date: | 15-May-2025 |
| Publisher: | Oxford University Press |
| Citation: | Motta S. et al. (2025) 'SOMMD: An R Package for the Analysis of Molecular Dynamics Simulations using Self-Organising Map', Bioinformatics, 0 (ahead of print), pp. 1 - 5. doi: 10.1093/bioinformatics/btaf308. |
| Abstract: | Motivation: Molecular Dynamics (MD) simulations provide critical insights into biomolecular processes but they generate complex high-dimensional data that are often difficult to interpret directly. Dimensionality reduction methods like Principal Component Analysis (PCA), Time-Lagged Independent Component Analysis (TICA) and Self-Organising Maps (SOMs) have helped in extracting essential information on functional dynamics. However, there is a growing need for a user-friendly and flexible framework for SOM-based analyses of MD simulations. Such a framework should offer adaptable workflows, customizable options, and direct integration with a widely adopted analysis software. Results: We designed and developed SOMMD, an R package to streamline MD analysis workflows. SOMMD facilitates the interpretation of atomistic trajectories through SOMs, providing tools for each stage of the workflow, from importing a wide range of MD trajectories data types to generating enhanced visualizations. The package also includes three example projects that demonstrate how SOM can be applied in real-world scenarios, including cluster analysis, pathways mapping and transition networks reconstruction. Availability: SOMMD is available on CRAN (https://CRAN.R-project.org/package=SOMMD) and on GitHub (https://github.com/alepandini/SOMMD). |
| Description: | Data availability:
The MD trajectory data required to run the examples in SOMMD are openly available on Figshare under CC-BY licence, and the accompanying R notebooks in the package include the code to automatically download and process these datasets. Supplementary information: Supplementary data are available at Bioinformatics online at: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaf308/8132949?searchresult=1#supplementary-data . Accepted manuscripts: Accepted manuscripts are PDF versions of the author’s final manuscript, as accepted for publication by the journal but prior to copyediting or typesetting. They can be cited using the author(s), article title, journal title, year of online publication, and DOI. They will be replaced by the final typeset articles, which may therefore contain changes. The DOI will remain the same throughout. |
| URI: | https://bura.brunel.ac.uk/handle/2438/31279 |
| DOI: | https://doi.org/10.1093/bioinformatics/btaf308 |
| ISSN: | 1367-4803 |
| Other Identifiers: | ORCiD: Alessandro Pandini https://orcid.org/0000-0002-4158-233X |
| Appears in Collections: | Dept of Computer Science Research Papers |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © The Author(s) 2025. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. | 970.46 kB | Adobe PDF | View/Open |
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