All Competitors

Single-cell foundation model that treats cells as tokens and tissues as sentences, encoding cell-cell relationships across 85M parameters.

Conversational agent that answers plain-language questions about DNA, RNA, and protein sequences by coupling a genomics encoder to a language model.

Family of medical multimodal models built on Gemini, adding uncertainty-guided web search, custom modality encoders, and long-context EHR reasoning.

Interpretable model of human transcription initiation that decomposes promoter activity into a minimal set of sequence rules at base-pair resolution.

Generalist medical vision-language foundation model with 40B parameters, spanning radiology, pathology, dermatology, retinography, and endoscopy.

Generalist cell instance segmentation for microscopy, pairing a SAM ViT-B encoder with flow-field decoding trained on 15K annotated images.

AI-designed CRISPR-Cas9 gene editor generated by protein language models trained on 1.2 million CRISPR operons and shown to edit the human genome.

Structure-based drug design that generates 3D ligands for a protein pocket entirely in the continuous parameter space of a Bayesian flow network.

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

Brain MRI foundation model pretrained with masked image modeling on roughly 57,000 multi-contrast head scans for brain tumor diagnosis.

Protein language model pairing sequence with quantized local-structure tokens via disentangled attention, for zero-shot variant effect prediction.

Protein language model that predicts which of twelve subcellular compartments and biomolecular condensates a human protein partitions into.

Microscopy foundation model for high-content screening, embedding genome-scale CRISPR knockout and compound perturbations from Cell Painting images.

Lightweight mixture-of-experts medical vision-language model routing visual question answering and image classification to domain-specific experts.

Drug combination synergy prediction across cancer cell lines, from LLM text embeddings of drugs and cell lines rather than structures or expression.

Swin transformer foundation model for fluorescence microscopy image restoration, unifying denoising, super-resolution, and volumetric reconstruction.

Genomic language model trained on metagenomic scaffolds that learns protein co-regulation and function by modeling gene context and operon structure.

Transformer language model for 5' UTR sequences that predicts mRNA translation efficiency, ribosome loading, and protein expression levels.

Multimodal large language model for 3D medical imaging that handles report generation, visual question answering, and segmentation on CT volumes.

Protein language model-based sequence search that detects remote homologs with threefold higher sensitivity than MMseqs2 at comparable speed.

Equivariant graph network that embeds a protein domain structure as a 128-dimensional vector, turning fold recognition into nearest-neighbour search.

Vision-language model for 3D chest CT that aligns whole volumes with radiology reports for zero-shot abnormality detection and case retrieval.

Separable 4D CNN that strips rotational streak artifacts from respiration-resolved cone-beam CT, processing all ten breathing phases in one pass.