DeepB3P: A transformer-based model for identifying blood-brain barrier penetrating peptides with data augmentation using feedback GAN
The interpretable analyses provided by DeepB<sup>3</sup>P offer valuable insights and enhance downstream analyses for BBBP identification. Moreover, the BBBP-like peptides generated by FBGAN hold potential as candidates for CNS drug development.
Authors
- Qiang Tang (ORCID: https://orcid.org/0000-0001-5489-3690)
- Wei Chen (ORCID: https://orcid.org/0000-0002-6857-7696)
Institutions
- Chengdu University of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Journal of Advanced Research
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1016/j.jare.2024.08.002
- Citations
- 12
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 2.81
Funders
- Natural Science Foundation of Sichuan Province