CGSDA: inferring snoRNA-disease associations via ChebNetII and GatedGCN
The implementation of CGSDA, along with relevant datasets, is publicly available at: https://github.com/cuntjx/CGSDA. This public release enables the research community to further validate and apply the framework, supporting advancements in computational identification of snoRNA-disease associations and facilitating progress in snoRNA-based therapeutic development, and ultimately benefiting human health.
Authors
- Yusong Lu
- Ting Zeng (ORCID: https://orcid.org/0000-0002-1435-3937)
- Shuilin Liao (ORCID: https://orcid.org/0000-0002-7067-2078)
- Zhanliang Wei
- Shanghui Lu (ORCID: https://orcid.org/0009-0008-2029-5332)
- Yi Zhang (ORCID: https://orcid.org/0000-0002-5589-8466)
- Le Li (ORCID: https://orcid.org/0000-0002-4999-2288)
- Rui Miao (ORCID: https://orcid.org/0000-0001-5292-4377)
- Yongfu Zou
Institutions
- Macau University of Science and Technology (MO)
- Zunyi Medical University (CN)
- The Second Nanning People's Hospital (CN)
- Nanning Normal University (CN)
- Hechi University (CN)
Publication Details
- Journal
- Frontiers in Genetics
- Published
- 2025-10-15
- DOI
- https://doi.org/10.3389/fgene.2025.1684484
- Primary Topic
- Cancer-related molecular mechanisms research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Office for Philosophy and Social Sciences