All Competitors

Instance segmentation for nervous-system tissue, trained only on biophysical simulations and applied to real brain, spinal cord and nerve sections.

Graph neural network counting recurring cell-type neighborhood motifs in spatial transcriptomics and proteomics, linking topology to phenotype.

Spatial virtual-cell foundation model that simulates single-cell gene expression at chosen positions in real human tumor tissue.

Cell type annotation from multiplexed tissue images, using a pretrained Vision Transformer ensemble that runs on new panels without fine-tuning.

Spatial gene expression prediction from H&E tumor histology, aligning a pathology foundation model with a single-cell RNA-seq foundation model.

Pathology image embeddings supervised by spatial transcriptomics instead of text captions, aligned over 697K image-gene expression pairs.

Spatial transcriptomics foundation model aligning histology with gene expression at spot and neighborhood scale for zero-shot tissue domain calling.

Histopathology foundation model aligned to spatial transcriptomics by a cross-modal ranking loss, embedding H&E patches without gene input.

Virtual multiplex immunofluorescence staining from H&E histopathology, imputing the expression and spatial localization of 50 protein biomarkers.

Cell phenotyping model for spatial proteomics using a language-informed vision transformer to classify cell types zero-shot across marker panels.

Spatial transcriptomics prediction from H&E slides, inferring spot-level expression and tumor microenvironment composition in breast cancer.

Spatial transcriptomics foundation model using cross-attention over niche ligand genes, pretrained on 4.1M deconvolved human Visium samples.

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

Fine-grained cell-type abundance prediction from H&E histology, transferring to unseen cohorts and large slide archives without any retraining.

Threshold-agnostic spot detection for 2D and 3D fluorescence microscopy, locating transcripts at subpixel accuracy via stereographic flow regression.

Spot detection for single-molecule RNA FISH and fluorescence microscopy, trained on a differentiable F1 approximation, needing no threshold tuning.

Virtual staining model that generates 11-marker spatially resolved protein multiplexes from routine H&E histopathology whole-slide images.

Generative toolkit that synthesizes six aligned immunohistochemistry markers from one H&E histopathology image, trained on unpaired stains.

Pseudo-membrane generator for fluorescence microscopy that synthesizes missing membrane staining from nuclei to improve single-cell segmentation.

Spatial proteomics imputation from a 7-plex immunofluorescence panel, generating in silico CODEX expression for 33 more biomarkers per cell.