With Evo 2, AI can model and design the genetic code for all domains of life

 

The DNA foundation model Evo 2 has been published in the journal Nature. Trained on the DNA of over 100,000 species across the entire tree of life, Evo 2 can identify patterns in gene sequences across disparate organisms that experimental researchers would need years to uncover. The machine learning model can accurately identify disease-causing mutations in human genes and is capable of designing new genomes that are as long as the genomes of simple bacteria.

Evo 2 was developed by scientists from Arc Institute and NVIDIA, convening collaborators across Stanford University, UC Berkeley, and UC San Francisco. The model's code is publicly accessible from Arc's GitHub, and is also integrated into the NVIDIA BioNeMo framework, as part of a collaboration between Arc Institute and NVIDIA to accelerate scientific research.

Arc Institute also worked with AI research lab Goodfire to develop a mechanistic interpretability visualizer that uncovers the key biological features and patterns the model learns to recognize in genomic sequences. The Evo team has shared its training data, training and inference code, and model weights, making it the largest-scale, fully open-source AI model to date.

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