AI techniques have facilitated the understanding of epitranscriptome distribution
N<sup>6</sup>-methyladenosine (m6A), the most prevalent internal mRNA modification in higher eukaryotes, plays diverse roles in cellular regulation. By incorporating both sequence- and genome-derived features, Fan et al.<sup>1</sup> designed a novel Transformer-BiGRU framework that achieves superior performance in computational m6A identification, thus demonstrating the potential of AI in genomic studies.
Authors
- Jia Meng (ORCID: https://orcid.org/0000-0003-3455-205X)
- Daiyun Huang (ORCID: https://orcid.org/0000-0002-3067-7165)
- Kunqi Chen (ORCID: https://orcid.org/0000-0002-6025-8957)
Institutions
- Fujian Medical University (CN)
- University of Liverpool (GB)
- Fudan University (CN)
- Xi’an Jiaotong-Liverpool University (CN)
Publication Details
- Journal
- Cell Genomics
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1016/j.xgen.2024.100718
- Citations
- 4
- Primary Topic
- RNA modifications and cancer
- Type
- article
- Field-Weighted Citation Impact
- 0.94
Funders
- National Natural Science Foundation of China
- Fujian Medical University