Biobox: a toolbox for biomolecular modelling

Rudden, Lucas S.P.; Musson, Samuel C.; Benesch, Justin L.P.; Degiacomi, Matteo T.

Abstract

Motivation The implementation of biomolecular modelling methods and analyses can be cumbersome, often carried out with in-house software re-implementing common tasks, and requiring the integration of diverse software libraries. Results We present Biobox, a Python-based toolbox facilitating the implementation of biomolecular modelling methods. Availability Biobox is freely available on https://github.com/degiacom/biobox, along with its API and interactive Jupyter notebook tutorials.

Citation

Rudden, L. S., Musson, S. C., Benesch, J. L., & Degiacomi, M. T. (2022). Biobox: a toolbox for biomolecular modelling. Bioinformatics, 38(4), 1149-1151. https://doi.org/10.1093/bioinformatics/btab785

• Journal Article Type: Article
• Acceptance Date: Nov 11, 2021
• Online Publication Date: Nov 15, 2021
• Publication Date: Feb 15, 2022
• Deposit Date: Nov 16, 2021
• Publicly Available Date: Nov 17, 2021
• Journal: Bioinformatics
• Print ISSN: 1367-4803
• Electronic ISSN: 1460-2059
• Publisher: Oxford University Press
• Peer Reviewed: Peer Reviewed
• Volume: 38
• Issue: 4
• Pages: 1149-1151
• DOI: https://doi.org/10.1093/bioinformatics/btab785
• Public URL: https://durham-repository.worktribe.com/output/1222790