An ensemble deep learning framework for multi-class LncRNA subcellular localization with innovative encoding strategy
Comparative analysis against commonly used sequence feature encoding methods and existing prediction models validates the effectiveness of MGBLncLoc, demonstrating superior performance. This research offers novel insights and effective solutions for predicting lncRNA subcellular localization, thereby providing valuable support for related biological investigations.
Authors
- Ruomei Yan
- Lixin Guan (ORCID: https://orcid.org/0000-0002-2554-5678)
- Mengshan Li (ORCID: https://orcid.org/0000-0003-4175-088X)
- Yan Yue (ORCID: https://orcid.org/0009-0004-9862-0431)
- Wenxing Hu (ORCID: https://orcid.org/0000-0003-2477-6383)
Institutions
- Gannan Normal University (CN)
Publication Details
- Journal
- BMC Biology
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1186/s12915-025-02148-4
- Citations
- 1
- Primary Topic
- Cancer-related molecular mechanisms research
- Type
- article
- Field-Weighted Citation Impact
- 0.94
Funders
- National Natural Science Foundation of China
- Education Department of Jiangxi Province