Single-Cell Analysis in the Age of Large Language Models

Join a comprehensive seminar and primer session exploring the intersection of Large Language Models (LLMs) and single-cell biological analysis. Begin with a primer led by Yale University Ph.D. student Syed Rizvi, who introduces the fundamentals of LLMs and biological foundation models, explaining their architecture, training processes, and applications in analyzing complex biological data. Continue with the main presentation by Yale University Assistant Professor David van Dijk, who demonstrates how biological systems operate similarly to language, featuring groundbreaking research projects including CINEMA-OT for causal inference in cytokine interactions, Cell2Sentence for transforming single-cell data into trainable formats for LLMs, and CaLMFlow for adapting LLMs to model continuous biological systems. Gain insights into how these innovative approaches are revolutionizing single-cell analysis and advancing biological research through the lens of computational linguistics and machine learning.