All Competitors

Trainable, open-source reimplementation of AlphaFold2 for protein structure prediction that matches its accuracy and runs 3-5x faster.

Deep learning framework predicting equilibrium distributions of molecular systems, enabling efficient ensemble generation and conformation sampling.

RNA language model pretrained on 23 million non-coding sequences with motif-level masking, then steered by predicted RNA type at fine-tuning.

Compact 22M-parameter ViT-S pathology foundation model pre-trained on 195M tiles, spanning subcellular segmentation to slide-level prediction.

Unified DNA, RNA, and protein foundation model with 1.8B parameters, pretrained across 169,861 species to learn the central dogma from sequence.

Diffusion-based structure prediction model for biomolecular complexes, spanning proteins with DNA, RNA, small molecules, ions, and modified residues.

Discrete generative model for antibody protein sequences combining MCMC walks on a smoothed energy landscape with one-step denoising jumps.

CLIP-style vision-language model for echocardiography, pretrained on echo videos and cardiologist reports for zero-shot cardiac interpretation.

Fine-tuned DNA language model that predicts differentially methylated cytosines in TET and DNMT3 knockout stem cells from sequence alone.

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.

Missense variant effect predictor that distills GEMME evolutionary scores into a small head over frozen protein language model embeddings.

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

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

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