All Competitors

A tri-modal foundation model unifying histology images, spatial transcriptomics, and biological language for zero-shot spatial biology and pathology reasoning.

A multi-organ foundation model aligning histology image features with spatial-transcriptomics gene expression across 13 organs for zero-shot virtual ST and survival prediction.

Latent flow-matching foundation model that predicts pan-cancer spatially-resolved single-cell gene expression directly from routine H&E histology slides.

A hierarchical multimodal foundation model integrating spatial transcriptomics and H&E histology for biological discovery and platform-agnostic clinical prediction.

A self-supervised, cell-centric pretraining strategy that distills morphology and microenvironment views of each cell into a unified embedding for virtual spatial omics from microscopy.

Bioptimus's first multimodal, multi-scale World Model for biology, integrating histology, transcriptomics, and clinical data from millions of patients into a unified embedding space.

An 80M-parameter histology Vision Transformer foundation model that predicts spatial gene expression from H&E tissue images and transfers to tumor detection and spatial clustering.

A 7-billion-parameter encoder-only DNA foundation model trained on 10.6 billion nucleotides from 796 species for functional genomics and synthetic biology.

BERT-based model pretrained on 15-state ROADMAP chromatin annotations across 127 human cell types to uncover chromatin-state motifs and predict gene expression.