Energy metric prediction for double insertion mutants via the RoseNet deep learning framework
The code used for training and evaluating the models in the study and the data underlying this article are available at https://github.com/hutchresearch/RoseNet.
Authors
- Brian Hutchinson (ORCID: https://orcid.org/0000-0002-5537-008X)
- Filip Jagodzinski (ORCID: https://orcid.org/0000-0001-7783-2241)
- Sarah Coffland (ORCID: https://orcid.org/0009-0005-7807-2703)
- Katie Christensen (ORCID: https://orcid.org/0009-0004-3270-7964)
Institutions
- Joint Global Change Research Institute (US)
- Pacific Northwest National Laboratory (US)
- Western Washington University (US)
Publication Details
- Journal
- Bioinformatics Advances
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1093/bioadv/vbae198
- Citations
- 1
- Primary Topic
- Genomics and Chromatin Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- National Science Foundation