All Competitors

Multimodal deep learning model that predicts protein-mediated chromatin contact maps and loops de novo from protein-binding profiles and sequence.

Foundation model for 3D genome architecture, using masked locus modeling over genome-wide contact profiles to capture chromosome-scale organization.

Multimodal 3D genome foundation model pairing Hi-C contact maps with epigenomic tracks, pretrained on over one million paired samples.

Hi-C resolution enhancement model combining a U²-Net with self-attention to recover TAD boundaries and chromatin loops from sparse contact maps.

Hi-C foundation model pretrained on 118 million contact submatrices, fine-tuned for loop detection, resolution enhancement and epigenomic prediction.

Hi-C contact map super-resolution that adds interaction frequencies imputed from DNase-seq accessibility so one cell line's model transfers to others.

Chromatin interaction prediction from DNA sequence alone, calling CTCF-, RNA Pol II- and Hi-C-associated loops between open chromatin regions.