Open access
Jun 2026
OmicsTransformer: self-supervised masked consistency and uncertainty-aware fusion for robust multi-omics prediction
OmicTransformer is presented, an end-to-end framework that projects each omics modality into latent patches, enforces masked semantic consistency through an Exponential Cosine Consistency Loss, models global patch dependencies with a Transformer encoder, and fuses modalities by sample-specific uncertainty.
Junxuan Feng, Bingshen Shan, Jie Deng et al.
· Bioinformatics · 0 citations