All Competitors

Histopathology foundation model for uterine malignancies that orders whole-slide morphology into continuous, progression-associated tumor states.

Graph attention foundation model for spatial transcriptomics that assigns spatial domains zero-shot across gene panels, tissues, and technologies.

Spatial genomics foundation model that predicts a cell's transcriptome from its neighbours and forward-simulates tissue response to perturbation.

Cell segmentation for image-based spatial transcriptomics that fuses RNA point clouds with any number of membrane and nuclear staining channels.

Self-supervised 3D masked autoencoder for volumetric fluorescence microscopy, aligned to ESM2 embeddings to predict protein localization.

Infers gene-centered chromatin interactions from bulk RNA-seq alone, mapping 3D genome changes across 12,347 tumor and normal transcriptomes.

Histopathology foundation model pretrained on 200 million H&E and immunohistochemistry tiles from more than 350,000 whole-slide images.

Generative microscopy foundation model that synthesizes in-silico fluorescence images of protein subcellular localization from amino-acid sequence.

Regulatory genomics model predicting cell-type-specific RNA-seq coverage from DNA sequence, unifying transcription, splicing, and polyadenylation.

Drug pair synergy prediction for rare cancer tissues, read from a language model's representation of a screening row written out as a sentence.

Variational autoencoder trained on scRNA-seq and applied frozen to impute unmeasured genes and denoise spatial transcriptomics profiles.

Virtual-cell model that compresses a transcriptome into eight discrete tokens in a reasoning LLM's vocabulary, predicting module-level drug response.

In-context learning model for cell-free RNA, meta-trained on synthetic tasks from a cfRNA structural causal model for few-shot cancer classification.

Enhancer models predicting cell-type-specific chromatin accessibility from DNA sequence, with a pretrained zoo and synthetic enhancer design tools.

Cell-type-specific gene expression prediction from DNA sequence, mapping Enformer epigenomic features to pseudobulk expression for cell-resolved TWAS.

Peptide-spectrum match rescoring for DDA proteomics, learned end to end from raw MS2 spectra and peptide sequence across 271 million PSMs.

Contrastive dual-encoder model for DIA proteomics, embedding peptides and spectra in a shared space for zero-shot peptide-spectrum matching.

Hi-C contact map super-resolution that adds interaction frequencies imputed from DNase-seq accessibility so one cell line's model transfers to others.

Chinese biomedical text encoder pretrained by masking whole medical entities and phrases, lifting clinical entity recognition and query understanding.

Metabolomic foundation model pretrained on UK Biobank NMR metabolite profiles, reused with a frozen backbone for aging, subtyping, and disease risk.

Transcriptomic perturbation prediction across unseen single and double gene knockdowns and unseen cell lines, driven by gene-gene knowledge graphs.

Generative language model for phenotype-driven drug discovery, proposing small-molecule structures from up- and down-regulated gene signatures.

Hierarchical language model for atlas-level cell-type annotation of scATAC-seq data that annotates new query datasets without retraining.