Session 6: Evo, A Foundation Model for Generative Genomics

DNA encodes the fundamental language for all living organisms. Recently, large language models have been used to learn this mysterious biological language to unlock a better understanding of this blueprint of life. Yet, learning from DNA has its distinct challenges over natural language - it’s extremely long, with the human genome over 3 billion nucleotides in length. It’s also highly sensitive to small changes, where a single point mutation can mean the difference between having a disease or not. Overcoming these technical challenges of modeling long sequences in DNA can lead to a deeper understanding of human disease, the creation of novel therapeutics, and the possibility to engineer life itself. This talk describes a research project aimed at developing a new line of long sequence language models that can reproduce the organization of DNA sequences from the molecular to the whole genome scale. The researchers seek to lead the ethical development of DNA sequence modeling and design, and to bring the innovation of AI systems for the betterment of human health. Learn more about other research supported by the Hoffman-Yee Research Grant program here: https://hai.stanford.edu/research/grant-programs/hoffman-yee-research-grants?section=2024-grant-recipients 00:00:00 Introduction 00:00:29 Lecture 00:30:26 Q&A