sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms
In conclusion, our newly developed sRNAdeep can help researchers identify bacterial sRNAs more precisely and can be freely available from https://github.com/pyajagod/sRNAdeep.git .
Authors
- Zhiyuan Yang (ORCID: https://orcid.org/0009-0006-0142-5301)
- Stephen Kwok‐Wing Tsui (ORCID: https://orcid.org/0000-0003-0686-4259)
- Tianyi Liu (ORCID: https://orcid.org/0000-0002-2624-7146)
- Jiawei Sun (ORCID: https://orcid.org/0009-0000-4532-9174)
- Weiye Qian (ORCID: https://orcid.org/0009-0005-3274-3575)
Institutions
- Chinese University of Hong Kong (HK)
- Hangzhou Dianzi University (CN)
Publication Details
- Journal
- BMC Genomics
- Published
- 2024-10-31
- DOI
- https://doi.org/10.1186/s12864-024-10951-6
- Citations
- 1
- Primary Topic
- RNA and protein synthesis mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- National Natural Science Foundation of China