All Competitors

T-cell clonal expansion detection from scRNA-seq alone, without paired TCR sequencing. Trained on 2.6M pan-cancer T cells, reaching 0.85-0.96 AUROC.

Protein conformational ensemble and dynamics generator using latent diffusion to sample all-atom MD trajectories and transition pathways.

Transcription factor binding site prediction fusing DNA sequence with TF protein embeddings by cross-attention, generalizing zero-shot to unseen TFs.

Centrosome segmentation framework chaining YOLOv11 detection, U-Net refinement, and StarDist cell boundaries across immunofluorescence and IHC tissue.

Generative antibody and nanobody design model that co-designs CDR sequences and antigen-bound structures for de novo design and affinity maturation.

Missense variant pathogenicity predictor that also ranks candidate diseases, aligning ESM-2 protein embeddings with PubMedBERT disease text.

Activation domain predictor scoring transcriptional activator strength from protein sequence, with a 20-model ensemble that reports uncertainty.

Protein language model that predicts which of eight lipid categories a protein binds from sequence alone, plus binding sites and mutation effects.

Linear B-cell epitope prediction from peptide sequence alone, pairing ProtT5 embeddings with an SVM trained on 222,030 curated IEDB peptides.

ECG foundation model on a bidirectional xLSTM backbone, pretrained with SimDINOv2 self-supervision to transfer across 12-lead, Holter and PPG traces.

Antimicrobial resistance risk predictor using ESM2 embeddings of single protein mutations to flag resistance variants across bacterial pathogens.

Gene Ontology prediction for malaria parasite proteins, trained on SAR supergroup structure embeddings with calibrated uncertainty and FDR control.

Nucleotide language model for short metagenomic reads, assigning taxonomic domain, coding potential, and reading frame from reads down to 100 bp.

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

Single-cell foundation model with rank and expression-aware input streams, pairing masked gene modeling with cell-level contrastive learning.

Discrete graph diffusion model for multi-property molecular generation, composing per-property score guidance over arbitrary condition subsets.

Multimodal tokenizer for antibody CDR loops, encoding backbone dihedrals and sequence as discrete tokens that plug into antibody language models.

Cancer genomics foundation model embedding clinical gene-panel mutations into tumor subtype vectors. Pretrained on 30,328 tumors and 8 networks.

Protein-ligand binding site prediction that ranks pocket residues and pocket center coordinates, staying accurate on AlphaFold-predicted structures.

Sequence-based multitask model predicting covalently ligandable cysteines and reversible ligand-binding residues across the human proteome.

Genomic foundation model that jointly encodes DNA sequence and functional omics tracks into unified single-nucleotide and interval-level embeddings.

Peptide-MHC class I binding predictor that scores force-field energy terms from modeled pMHC structures, holding precision on rare HLA alleles.

Antibiotic resistance gene detection in metagenomes, pairing frozen ESM-1v embeddings with light classifier heads for drug class and mechanism.