GraphCPP: The new state‐of‐the‐art method for cell‐penetrating peptide prediction via graph neural networks
These findings indicate the potential of GNN-based models to improve CPP penetration prediction and it may contribute towards the development of more efficient drug delivery systems.
Authors
- István M. Mándity (ORCID: https://orcid.org/0000-0003-2865-6143)
- Balázs Balogh (ORCID: https://orcid.org/0000-0001-7282-7283)
- Attila Imre (ORCID: https://orcid.org/0009-0004-0110-8395)
Institutions
- Semmelweis University (HU)
- HUN-REN Research Centre for Natural Sciences (HU)
Publication Details
- Journal
- British Journal of Pharmacology
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1111/bph.17388
- Citations
- 22
- Primary Topic
- RNA Interference and Gene Delivery
- Type
- article
- Field-Weighted Citation Impact
- 5.14
Funders
- European Commission
- Hungarian Scientific Research Fund
- National Research, Development and Innovation Office