Aegis: a transformer-based deep learning framework for the accurate identification of anticancer peptides
Overall, our study demonstrates the exceptional potential of transformer-based deep learning for ACP identification, laying a foundation for future computational screening and the clinical development of novel ACPs.
Authors
- Zexu Zhou
- Yijie Wei
- Hui Ding (ORCID: https://orcid.org/0000-0002-6875-1172)
- Yang Liu
- Sijia Xie (ORCID: https://orcid.org/0000-0002-9588-1757)
- Lijun Xie (ORCID: https://orcid.org/0000-0002-3618-8549)
- H C Yang
- Feitong Hong
- Hao Lyu
- Chengbing Huang
- Fuying Dao
- Xinwei Luo
Institutions
- University of Electronic Science and Technology of China (CN)
- Nanyang Technological University (SG)
- Aba Teachers University (CN)
- Quzhou University (CN)
- Yangzhou University (CN)
Publication Details
- Journal
- BMC Biology
- Published
- 2026-01-26
- DOI
- https://doi.org/10.1186/s12915-026-02520-y
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00