All Competitors

Zero-shot tumor segmentation on CT and MRI that reads text-prompted anomaly attention maps out of a frozen medical foundation diffusion model.

Retrosynthesis and reaction prediction LLM that jointly learns molecular fragmentation and recombination from a 4.4M-instruction chemistry corpus.

Sparse-view CBCT reconstruction foundation model pretrained on 8,407 CT volumes, recovering full 3D anatomy from as few as six X-ray projections.

Protein model accuracy estimation for single chains and complexes, predicting per-residue lDDT, interface QS-score, and overall fold TM-score.

Antibody foundation model generating paired sequences with genetic and developability metadata for labelling, humanisation, and library design.

Anticancer protein prediction from sequence with a fine-tuned ESM-2 650M classifier; a BLAST hybrid raises validation AUC to 0.91.

Generative diffusion model that samples biomolecular conformational ensembles for proteins, RNA, and ligands in hours instead of millisecond-scale MD.

Physics-guided all-atom diffusion model for protein-ligand complex prediction, reaching 95.3% success on PoseBusters redocking with a known pocket.

Generalist cell segmentation model pairing SAM's ViT-L encoder with Cellpose flow fields, outperforming average human annotators on its benchmark.

Brain MRI segmentation foundation model trained on 66,000+ image-label pairs across 14 MRI sub-modalities, with a hypergraph dynamic adapter.

Genomic prediction model for plant and animal breeding, pretrained entirely on simulated populations and deployed with no training or tuning.

Peptide-MHC structure prediction by SE(3)-equivariant diffusion, sampling 10 Cα conformations in under 6 seconds at 0.45 Å best-of-10 RMSD.

Single-cell foundation model inferring cis-regulatory relationships from scRNA-seq and scATAC-seq, pretrained on an atlas of 1.3 million cells.

Universal foundation model that jointly generates diagnostic text and segments the corresponding targets across ten biomedical imaging modalities.

De novo protein design model using flow matching for binder, motif scaffolding, and symmetric generation, with wet-lab-validated binders.

Alignment-free biosynthetic gene cluster detection and annotation from ESM-2 gene embeddings in genomic context, up to 102x faster than antiSMASH.

Generative single-cell foundation model trained on 112 million cells from 12 species, autoregressively modeling gene identities and expression counts.

Vision transformer that regresses Ki-67-positive and -negative nuclei counts in breast histopathology and scores the index from H&E slides alone.

RNA secondary structure prediction that turns phylogenetic compensatory-substitution evidence into attention priors over frozen RiNALMo embeddings.

Kinase-substrate specificity prediction from sequence alone, using ESM-2 embeddings to score phosphorylation across whole mammalian kinomes.

Multimodal physiological foundation model spanning EEG, ECG, EOG, and EMG that keeps working when arbitrary modalities are missing at inference time.

Single-cell foundation model inferring context-specific protein-protein interactions from cancer transcriptomes via a variational graph autoencoder.

Single-cell type annotation pairing a CellMarker-derived knowledge graph with multi-agent LLM retrieval, generalizing across 11 tissue types.