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Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks
- Source :
- Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Portfolio, 2021.
-
Abstract
- Computational methods are becoming an increasingly important part of biological research. Using the Rosetta framework as an example, the authors demonstrate how community-driven development of computational methods can be done in a reproducible and reliable fashion.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 12
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.7ccba8c202cd473d906c246ef7b2eb77
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-021-27222-7