All Competitors

Histopathology foundation model for whole-slide cancer diagnosis, covering 19 common cancer types and 205 clinical diagnostic tasks.

Fragment-protein interaction model trained on cellular chemoproteomics, pairing ESM-2 residue embeddings with bilinear attention over ligand atoms.

Unsupervised gene finder that annotates any eukaryotic genome from a raw FASTA file, using a differentiable hidden Markov layer inside the network.

Structure scoring model for antibody-antigen and protein-ligand complexes, built on one frozen geometry-aware backbone reused across scoring tasks.

Biomolecular complex structure prediction without multiple sequence alignment, for protein-protein, protein-ligand and protein-nucleic acid binding.

Volumetric cell segmentation for 3D fluorescence microscopy, pretrained on 5.1 TB of unlabeled volumes and generalizing across species and imaging.

Modality-agnostic transformer pretrained by masked abundance reconstruction on 48,837 proteomics profiles reprocessed from 1,397 PRIDE projects.

Tissue reconstruction model placing dissociated single cells into spatial coordinates by predicting pairwise distances in a learned embedding space.

Protein structure prediction from multiple sequence alignments, trained across MSA depths so one model spans deep alignments and orphan proteins.

Multi-task cellular foundation model predicting drug sensitivity, perturbation expression and drug-protein binding from one pretrained checkpoint.

Transmembrane topology predictor that calls re-entrant regions and interfacial helices, and assigns each protein to one of 17 biological membranes.

Ordered-water prediction for protein structures by flow matching, adding the crystal symmetry mates that coordinate waters at lattice contacts.

Protein perturbation model conditioning substitution-effect prediction on a learned protein-level regime coordinate over 202 million sequences.

Single-cell foundation model pretrained on human brain organoids that predicts transcriptome-wide responses to knockdown of any protein-coding gene.

Conditional diffusion model for 5' UTR and UTR-CDS junction design, targeting ribosome load, folding energy and codon adaptation at sampling time.

NMR foundation model that turns 1D 1H spectra into reusable embeddings, with a shared encoder serving denoising, peak detection, and retrieval.

Protein language model embedding enrichment that injects structural and dynamical signal as a low-energy residual, using sequence alone at inference.

Sequence-only dual-encoder contrastive model that ranks whole molecule libraries against a protein target without 3D structures or per-pair scoring.

EEG foundation model pairing masked contextual modelling with cross-view invariance learning over 11,000 hours of routine clinical recordings.

Protein language model that supervises embedding geometry with inter-residue contacts, so representation distance tracks physical distance.

Antifreeze protein classifier over frozen ESM-2 embeddings, trained only on sequences whose antifreeze activity was measured in the lab.

Longitudinal multimodal patient foundation model for oncology, fusing clinical records, DNA, RNA, and H&E pathology into one patient-state embedding.

Long-context RNA foundation model reading whole mRNA transcripts at single-nucleotide resolution, pretrained at a native 10,240 nt context.