All Competitors

Multimodal biomedical framework aligning frozen single-cell and protein model encoders to an LLM's embedding space for zero-shot reasoning.

Protein structure tokenizer that maps 3D backbones to discrete tokens with an SE(3)-equivariant encoder preserving orientation and chirality.

Diffusion model for multichannel fluorescent cell microscopy, generating morphologically plausible images aligned to OpenPhenom phenotypic embeddings.

Pan-tissue quality-control model that predicts RNA integrity and autolysis from H&E whole-slide images using frozen UNI foundation model embeddings.

Predicts single-cell scRNA-seq coverage and scATAC-seq insertion profiles from DNA sequence, adapting the Borzoi trunk with a cell-specific decoder.

Potts-model inverse folding that conditions on a structural ensemble rather than a single backbone, improving designability and self-consistency.

Multimodal scientific foundation model unifying protein, DNA/RNA, and small-molecule structure in one token vocabulary for cross-domain reasoning.

Predicts virtual single-cell spatial transcriptomics from H&E histology using frozen pathology foundation models and spot-level supervision.

Neuro-oncology foundation model for brain tumor MRI, using distributionally robust pretraining for molecular subtyping and survival prediction.

Self-supervised foundation model for 3D brain MRI, learning transferable anatomical representations from unlabeled scans for disease classification.

Cryo-EM and cryo-ET map enhancement model that sharpens density maps with a Mamba-based dual-branch UNet and local resolution-guided learning.

Protein binder design model post-trained from a multimodal protein language model to bind proteins, peptides, small molecules, and nucleic acids.

Modality-agnostic foundation model for human brain imaging that runs five core neuroimaging tasks across uncalibrated CT and MRI without retraining.

Biological reasoning language model that post-trains Qwen3 with reinforcement learning from verifiable rewards for drug-discovery tasks.

Single-cell foundation model for yeast that injects regulatory network priors into transformer attention for zero-shot and fine-tuned analysis.

Reasoning language model post-trained on virtual cell simulations, answering questions about gene perturbations and their effects in natural language.

Multimodal foundation model predicting genome-wide binding of chromatin-associated proteins from protein sequence, DNA sequence, and chromatin state.

Self-supervised bioacoustic audio encoder that turns animal-sound recordings into transferable embeddings for species classification and detection.

Histology vision transformer with 80M parameters that predicts spatial gene expression from H&E tissue images and transfers to tumor detection.

Tri-modal contrastive model aligning protein structure, sequence, and text in a shared space for zero-shot cross-modal retrieval and classification.

RNA foundation model pretrained jointly on sequences and secondary structures for structure prediction, homology and splice site classification.

Multimodal, retrieval-augmented protein foundation model that learns family-specific evolutionary constraints with optional structure conditioning.

Biomedical named entity recognition transformers, with task-specialized checkpoints for chemicals, diseases, genes, proteins, species, and anatomy.

Proteome-scale protein language model whose representations enable zero-shot protein-protein interaction and gene essentiality prediction.