All Competitors

Generative imaging model simulating single-cell fluorescence microscopy for all 12,800 human proteins in the Human Protein Atlas.

Single-cell foundation model that fuses scRNA-seq profiles with text, pairing a cell encoder with an LLM for cell annotation and clustering.

Single-cell analysis model driven by plain-language instructions, covering cell type annotation, pseudo-cell generation, and drug response prediction.

Transformer foundation model pretrained on 110M single-cell and spatial transcriptomics profiles, transferring spatial context to dissociated cells.

Diffusion model predicting single-cell responses to genetic or drug perturbations, generating over distributions to capture population variability.

Drug-conditional adapter inside a frozen single-cell foundation model, predicting transcriptional responses to unseen drugs and cell lines.

Virtual spatial transcriptomics foundation model predicting pan-cancer, spatially-resolved single-cell gene expression from H&E histology slides.

Resolution enhancement for sparse single-cell Hi-C contact matrices, using a cascading residual GAN with self-attention over chromatin loci.

Molecule generation conditioned on single-cell transcriptomes, designing cell-type-specific compounds that revert diseased cell states.

Multi-modal, multi-task biological foundation model trained on 2 billion samples spanning proteins, small molecules, and single-cell gene expression.

Single-cell foundation model using tabular attention over context cells to predict responses to arbitrary perturbations without fine-tuning.

Digital hematopathology foundation model unifying blood-cell detection, classification, segmentation, and visual question answering.

Single-cell multiomic foundation model that transfers pan-cancer RNA-ATAC regulatory structure into RNA-only tumour datasets via low-rank adapters.

Subject-level disease prediction from scRNA-seq, pairing cell-type-grouped scGPT pretraining with a Reactome pathway-constrained decoder.

Single-cell foundation model pretrained by federated learning, modeling expression as a cell-by-gene table rather than an ordered gene sentence.

Single-cell latent diffusion model fine-tuned on 14.5 million CD4+ T cells to simulate transcriptomic effects of single-gene perturbations.

Single-cell ATAC-seq foundation model that builds cell representations from non-zero chromatin peaks via peak-to-gene alignment.

Single-cell foundation model for Drosophila that generates hierarchical cell-type annotations on new scRNA-seq datasets without any fine-tuning.

Cell type annotation model mapping human single-cell and spatial transcriptomes onto one hierarchical typology of 381 types across 23 tissues.

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

Gene representation framework fusing DNA, transcript, protein, text, and single-cell embeddings into one latent space that survives missing views.

Diffusion model for synthesizing single-cell RNA-seq data, with guided generation of specific cell types, rare cells, and developmental trajectories.

Single-cell multi-omics foundation model whose three-stage pretraining and distillation yield RNA-and-ATAC-aware embeddings from RNA-only input.