DNAmBERT: a transformer-based model for non-invasive cancer diagnosis using DNA sequence and methylation data
DNAmBERT, a Transformer-based deep learning framework designed to jointly model DNA sequence context and read-level methylation haplotype structure from cfDNA methylation sequencing data, indicates that integrated sequence–haplotype representation learning provides an accurate and scalable approach for cfDNA-based mult...