Invited speaker: Eric P. Xing (Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels)

Title: Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels

Abstract: Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating, and Programming Biology at All Levels: At the core of medicine, pharmacy, public health, longevity, agriculture, and environment, is biology at work. Biology in the physical world is too complex to manipulate and always expensive and risky to tamper with. In this talk, I present a vision of using AI to model and simulate biology and life. I will layout an engineering viable approach to construct an AI-Driven Digital Organism (AIDO), leveraging self-supervised pretraining and adaption of large-scale foundation models, and I introduce some early results including 5 SOTA foundation models for DNA, RNA, Protein, Structure, and Single Cell, respectively, and their abilities to tackle biological problems at the full spectrum of granularities, from sequence, to structure, to network, to phenotype, to diseases, and to drug responses. We envision that AIDO opens up a safe, affordable, and high-throughput alternative platform for predicting, simulating and programming biology at all levels from molecules to cells to individuals, and is poised to trigger a new wave of better-guided wet-lab experimentation and better-informed first-principle reasoning, which can eventually help us better decode and improve life.