HPOseq: a deep ensemble model for predicting the protein-phenotype relationships based on protein sequences
The results of 5-fold cross-validation reveal that HPOseq outperforms seven baseline methods for predicting protein-phenotype relationships. Moreover, we conduct case studies from the points of phenotype annotation and protein analysis to verify the practical significance of HPOseq.
Authors
- Quan Na (ORCID: https://orcid.org/0000-0002-7315-0283)
- Xuehua Bi (ORCID: https://orcid.org/0009-0004-4861-1588)
- Kai Zhao (ORCID: https://orcid.org/0000-0002-5448-9919)
- Zhongzhong Ji (ORCID: https://orcid.org/0000-0003-0562-2477)
- Guanglei Yu (ORCID: https://orcid.org/0000-0003-0954-3397)
- Linlin Zhang (ORCID: https://orcid.org/0000-0002-0823-7825)
- Yuheng Li (ORCID: https://orcid.org/0000-0002-1865-1122)
Institutions
- Central South University (CN)
- Xinjiang Medical University (CN)
- Xinjiang University (CN)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1186/s12859-025-06122-3
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Xinjiang