MIA: David van Dijk,Single-cell analysis in the age of LLMs; Primer: Syed Rizvi

Models, Inference and Algorithms, October 16, 2024 Broad Institute of MIT and Harvard Meeting: Single-cell analysis in the age of LLMs David van Dijk Assistant Professor, Dept. of Computer Science & Dept. of Int. Medicine, Yale University In this talk, I will argue that biology itself operates like a language, where systems like the immune response communicate through combinatorial interactions, much like words forming sentences. I will present recent work from our lab, starting with CINEMA-OT, a causal inference method applied to combinatorial cytokine stimulation, revealing nonlinear interactions between cytokines. I will then focus on Cell2Sentence, a project that transforms single-cell data into 'cell sentences' to train LLMs for generating and predicting cellular behaviors. Finally, I will briefly discuss CaLMFlow, where LLMs are adapted to model continuous systems, highlighting their versatility beyond discrete language tasks. Together, these projects illustrate how LLMs are advancing single-cell analysis and biological research. Relevant Resources: CINEMA-OT: https://www.nature.com/articles/s4159... Cell2Sentence: https://www.biorxiv.org/content/10.11... CaLMFlow: https://arxiv.org/abs/2410.05292 Primer: Large Language Models and Biological Foundation Models Syed Rizvi Ph.D. student Department of Computer Science Yale University In the primer part of the seminar, we will explore Large Language Models (LLMs) and biological foundation models, covering their architecture, training, and how they are being adapted to analyze complex biological data, such as single-cell genomics. This section will introduce the idea that these models can help us decode the 'language' of biology. For more information visit: https://www.broadinstitute.org/talks/... Copyright Broad Institute, 2024. All rights reserved.