A self-supervised DNA foundation model with collapse-resistant multimodal fusion
Genomic foundation models pretrained on DNA sequence have achieved strong performance across a range of tasks, but sequence-only representations cannot fully capture regulatory information reflected by additional DNA-centric modalities. Existing multimodal genomic models are often optimized for specific prediction tasks rather than for learning reusable embeddings shared across downstream…
We haven't written up this one. bioRxiv has the full story — the link below goes straight to it.
