InterLabelGO+: unraveling label correlations in protein function prediction
The source code and datasets for InterLabelGO+ are freely available on GitHub at https://github.com/QuanEvans/InterLabelGO. A web-server is available at https://seq2fun.dcmb.med.umich.edu/InterLabelGO/. The software is implemented in Python and PyTorch, and is supported on Linux and macOS.
Authors
- Quancheng Liu (ORCID: https://orcid.org/0000-0001-9552-1738)
- Lydia Freddolino (ORCID: https://orcid.org/0000-0002-5821-4226)
- Chengxin Zhang (ORCID: https://orcid.org/0000-0001-7290-1324)
Institutions
- University of Michigan (US)
Publication Details
- Journal
- Bioinformatics
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1093/bioinformatics/btae655
- Citations
- 7
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 2.53
Funders
- National Science Foundation
- National Institute of Allergy and Infectious Diseases
- Office of Advanced Cyberinfrastructure