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Where innovation meets progress

AlphaGenome

AlphaGenome

DeepMind’s AI for Understanding the Genome

What is AlphaGenome?

AlphaGenome is Google DeepMind’s breakthrough AI model purpose-built to decode the genetic “dark matter” of our DNA, especially the mysterious, non-coding regions that make up 98% of the genome. Unlike earlier genome AIs that focused mainly on protein-coding segments, AlphaGenome can process up to 1 million base pairs of DNA in one pass, predicting the molecular impact of both common and rare variants across protein-coding and regulatory sequences. This unified model helps researchers interpret how DNA changes affect gene expression, splicing, and chromatin activity, powers that are foundational for advances in disease research, drug discovery, and personalized medicine.

Key Features of AlphaGenome

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Ultra-Long Sequence Analysis

  • Analyzes up to 1M base pairs, including non-coding regions.

Variant Effect Prediction

  • Predicts mutation impacts on gene expression, splicing, and regulation across tissues.

High-Resolution Function Modeling

  • Delivers base-pair–level predictions for gene features and regulatory signals.

Hybrid Deep Learning Architecture

  • Uses CNNs for local patterns and transformers for long-range DNA interactions.

State-of-the-Art Benchmarking

  • Outperforms other sequence-to-function models on 24/26 key genomics tasks.

Research-Ready Deployment

  • Accessible via API for academic research; broader applications planned.

Powered by Multi-Omics Data

  • Trained on large-scale datasets (ENCODE, GTEx, 4D Nucleome, FANTOM5) for broader accuracy.

Use Cases of AlphaGenome

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Disease Genetics & Cancer Research

  • Identify and prioritize variants that impact gene regulation, pinpoint splicing mutations, and understand the genetic basis of complex diseases.

Functional Genomics in Biotech

  • Guide experimental design for CRISPR gene editing, and speed the discovery of regulatory elements and disease-linked loci.

Pharmaceutical Target Discovery

  • Simulate effects of thousands of variants in silico, streamlining drug target validation for biotech and pharma R&D.

Large-Scale GWAS Interpretation

  • Enhance the interpretation of genome-wide association study (GWAS) data by predicting which variants are likely to have functional consequences.

Personalized Genomics & Precision Medicine

  • Provide insights into variant pathogenicity in individual genomes, accelerating actionable findings in clinical genetics.

AlphaGenome

vs

Previous and Other Genomics AI

Feature AlphaGenome Previous Genomics AI Other Seq-to-Function Models
Input Sequence Length Up to 1M base pairs ≤32K base pairs Varies (often ≤100K)
Variant Effect Prediction Yes (multi-modal) Limited (single output) Partial
Non-Coding “Dark Matter” Support Yes (98% of genome) Minimal Minimal
Model Architecture CNN + Transformer CNN only CNN or RNN
Benchmark Accuracy SOTA (24/26 tasks) Moderate Moderate - High
Deployment Research API (now) Open/source Varies

The Future

of AI in Genomics

As datasets grow and clinical genomics advances, unified AI models like AlphaGenome will underpin precision medicine, functional annotation, and the next era of molecular diagnostics, turning DNA data into actionable scientific insight.

Get Started with AlphaGenome

AlphaGenome is now available to the global research community via API (for non-commercial use), with commercial and clinical uses on the roadmap. Visit DeepMind’s AlphaGenome portal for technical docs, access requests, and live updates.

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