Models (10)
Google DeepMind model that predicts thousands of functional genomic tracks at single base-pair resolution from megabase-scale DNA sequences. Open-sourced with public API access in January 2026.
A family of sensor-language foundation models from Google that aligns wearable biosignals with natural language for zero-shot recognition, retrieval, and captioning.
Unified diffusion-based model predicting structures of protein complexes with nucleic acids, small molecules, ions, and modified residues with atomic accuracy.
Google's family of medical multimodal models built on Gemini, adding uncertainty-guided web search, custom modality encoders, and long-context EHR reasoning.
AlphaFold-derived model from Google DeepMind that predicts missense variant pathogenicity across the entire human proteome with AuROC 0.940 on ClinVar.
A self-supervised foundation model for retinal images, pretrained on 1.6M fundus and OCT scans to detect ocular and systemic disease.
Google's generalist multimodal biomedical AI that encodes clinical text, medical images, and genomics with a single set of weights across 14 tasks.
Transformer model that predicts gene expression and regulatory activity from 200kb DNA sequences, capturing enhancer-promoter interactions up to 100kb away.
DeepMind's extension of AlphaFold 2 for predicting protein complex structures, using paired MSA processing and ipTM scoring to model multimeric assemblies.
AI system that predicts 3D protein structures from amino acid sequences with atomic accuracy. Won CASP14 with a median GDT score of 92.4.