Identifying RNA ac4C Modification Sites via Pseudo-Nucleotide Fingerprint Encoding and Multi-Scale Feature Integration.
DFM-ac4C, a novel computational framework designed for the accurate prediction of ac4C modification sites, significantly outperforms existing models, achieving outstanding predictive metrics, and underscores DFM-ac4C's effectiveness as a robust and efficient tool for RNA ac4C site identification.