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Evo 2

A foundation model for genomic understanding

Evo 2, a powerful biomolecular AI model, provides insights into DNA, RNA and proteins across diverse species.

Top comment

Hi everyone!

Sharing Evo 2, a new foundation model for biomolecular sciences, now available on NVIDIA BioNeMo. This is a collaboration between the Arc Institute, Stanford, UC Berkeley, UCSF, and NVIDIA. It's significant because it's trained on a massive dataset – nearly 9 trillion nucleotides of DNA, RNA, and protein sequences from across the tree of life.

Key aspects:

🧬 Genomic Scale: Trained on an enormous dataset covering diverse species.
🔬 Multimodal: Understands DNA, RNA, and protein sequences.
🧠 Long Context: Can process sequences up to 1 million nucleotides at once.
🚀 Powerful Architecture: Uses a "StripedHyena 2" architecture for efficiency.
✅ Open Components: Key parts, including fine-tuning, are available via the open-source NVIDIA BioNeMo Framework.
🔓Available as NVIDIA NIM microservice.

They've already shown it can predict the effects of gene mutations with high accuracy, and even design functional CRISPR-Cas systems. It's a powerful tool for anyone working with biological sequence data.

So, while AlphaFold primarily predicted existing structures, Evo 2 opens the door to designing entirely new biological sequences for things like drug discovery, agriculture, and materials science. What new possibilities does this unlock?