BiToxNet: a deep learning framework integrating multimodal features for accurate identification of neurotoxic peptides and proteins
Overall, BiToxNet provides a powerful and generalizable computational framework for the accurate identification of neurotoxic peptides and proteins. By effectively integrating evolutionary and biochemical information through bilinear attention, BiToxNet offers a valuable tool for neurotoxin screening and protein drug safety assessment, and presents a distinctive modeling strategy applicable to a wide range of biological sequence analysis tasks.
Authors
- Xiukun Lin (ORCID: https://orcid.org/0000-0002-0306-4953)
- Xi He (ORCID: https://orcid.org/0000-0003-3902-028X)
- Lantian Yao
- Tzong-Yi Lee
- Jiahui Guan
- Chang Liu
- Leyi Wei
- Feng Wang
- Peilin Xie
Institutions
- National Yang Ming Chiao Tung University (TW)
- Xiamen University (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- Macao Polytechnic University (MO)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- BMC Biology
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1186/s12915-026-02508-8
- Primary Topic
- vaccines and immunoinformatics approaches
- Type
- article
- Field-Weighted Citation Impact
- 0.00