miCDER: a context-aware transformer model for joint miRNA-disease entity and multi-level regulatory relation extraction
Our proposed miCDER model can serve as an effective tool for extracting fine-grained regulatory information from biomedical texts. The resultant knowledge graph constitutes a significant resource for the advancement of research on diseases related to microRNA.
Authors
- Jiangcheng Shi (ORCID: https://orcid.org/0000-0001-9934-4556)
- Jinhao Su (ORCID: https://orcid.org/0009-0008-6466-1410)
- Lijun Wang (ORCID: https://orcid.org/0000-0002-5695-4669)
- Lixue Liu (ORCID: https://orcid.org/0009-0004-5973-1067)
Institutions
- Tiangong University (CN)
Publication Details
- Journal
- BMC Genomics
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1186/s12864-025-12342-x
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00