All Competitors

Protein dynamics model predicting per-residue covariances and residue-residue coupling from a static structure for fast RMSF and ensemble generation.

Image-to-image translation from label-free phase-contrast microscopy to H&E-like images, so pretrained histopathology models run on live cells.

Structure-based drug design model generating 3D ligands in a protein pocket with interaction-guided flow matching and a learned atom-count predictor.

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

Structure-based drug design model generating 3D ligands in protein pockets under gradient guidance for affinity, synthesizability, and selectivity.

Histopathology classifier separating atypical from normal mitotic figures, LoRA-adapting a DINOv3 vision transformer with 1.3M trainable parameters.

Protein degrader design framework that mines fragment-target data to build PROTACs and predicts degradation potency (DC50) and maximal degradation.

Generative antibody model that produces light-chain sequences conditioned on a heavy chain, pairing a RoBERTa encoder with a GPT-2 decoder.

Antibody-antigen binding free energy predictor fusing ESM-2 sequence embeddings with persistent homology and interface geometry via cross-attention.

Energy-based flow matching for 3D molecular structure, using an idempotent predict-and-refine map for protein backbone generation and ligand docking.

Patient-level representation learning from scRNA-seq: a transformer set encoder with a diffusion decoder, fine-tuned for clinical prediction.

Simplex diffusion model for discrete sequence generation, with released checkpoints for DNA enhancer design and de novo protein sequence design.

Predicts residue-residue dynamic contact maps from a single sequence, matching molecular dynamics ensemble methods at a fraction of the compute.

Codon language model trained with synonymous-codon-constrained masking, so its embeddings encode nucleotide-level signal, not amino acid identity.

Generalist MRI vision-language foundation model that handles reconstruction, segmentation, abnormality detection, and report generation in one model.

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

Vision-language foundation model for kidney cancer CT, covering zero-shot malignancy diagnosis, report generation, and recurrence risk prediction.

Generative model that restores cytoplasm-enriched genes lost in snRNA-seq, recovering cell-cell communication signals from raw nuclear counts.

Protein-ligand binding model that embeds ligands, pockets, and sequences in hyperbolic space, unifying virtual screening and affinity ranking.

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

Multi-organ segmentation network jointly trained on 10 CT and OCT datasets, reaching 0.83 mean Dice on the RETOUCH retinal fluid challenge.

All-atom protein structure diffusion models for motif scaffolding and hotspot-conditioned complex generation, at 22M parameters.

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