A drug response prediction method for single-cell tumors combining attention networks and transfer learning
ATSDP-NET identifies critical genes linked to drug responses, confirming its predictions through differential gene expression scores and gene expression patterns. This method provides valuable insights into the mechanisms of drug resistance and offers potential for developing personalized treatment strategies.
Authors
- Haixia Long (ORCID: https://orcid.org/0000-0003-2202-3820)
- Yusheng Li
- Si-Lin Sun
- B. Zhou (ORCID: https://orcid.org/0000-0002-7986-9045)
- ShengZheng Liu (ORCID: https://orcid.org/0009-0008-0740-002X)
Institutions
- Hainan Normal University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-08-21
- DOI
- https://doi.org/10.3389/fmed.2025.1631898
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Hainan Normal University