ProteinFormer: protein subcellular localization based on bioimages and modified pre-trained transformer
ProteinFormer and its GL-ProteinFormer variant show superior performance over existing convolution-based methods. By fusing biological images with transformer-based global feature modeling, the proposed approach offers a robust and efficient solution for protein subcellular localization, especially in data-limited settings.
Authors
- Huiping Liao
- Cuixiang Lin
- Xu An (ORCID: https://orcid.org/0000-0003-3386-5521)
- Guosheng Han (ORCID: https://orcid.org/0000-0002-7712-6213)
- Yixin Li (ORCID: https://orcid.org/0009-0002-9290-5300)
- Xianhua Xie
- Wanqiang Chen
Institutions
- Gannan Normal University (CN)
- Xiangtan University (CN)
Publication Details
- Journal
- BMC Genomics
- Published
- 2025-11-07
- DOI
- https://doi.org/10.1186/s12864-025-12194-5
- Citations
- 1
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.63
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangxi Province