June Data Sharing and Reuse Seminar

Fuhai Li, Ph.D., will present "Transformative AI for Deep Mining of Omics and Literature Data" from 12:00 p.m.–1:00 p.m. EDT.

About the Seminar

Transformative AI models are powerful tools for large-scale mining of biomedical data.  In this talk, I will present novel approaches that we have developed to combine large language models (LLMs) with graph-based AI to integrate and analyze vast omics datasets for identifying disease targets, mapping signaling pathways, and predicting effective drug combinations. The key component of this novel AI system is the text-numeric graph (TNG), a structure in which graph entities and associations carry both textual and numeric attributes. I will also introduce an AI multi-agent system that we have developed to accelerate biomedical discovery by unifying omics data analysis, literature-based deep search, and reasoning to generate novel scientific hypotheses. I will then showcase the applications of these novel AI tools with analysis of heterogeneous pharmacogenomics data for cancer research.

About the Speaker

Fuhai Li, Ph.D. Associate Professor, School of Medicine and Computer Science & Engineering, Washington University

Dr. Fuhai is an Associate Professor in the Institute for Informatics (I2), School of Medicine and Computer Science & Engineering (CSE), Washington University in St. Louis (WashU).  His research interests lie in developing large-scale and complex graph- and AI-based approaches to integrating and mining massive diverse and heterogeneous multi-modality data for identifying biomarkers, uncovering signaling mechanisms of diseases and discovering novel synergistic drugs and combinatory therapies. Before joining WashU in 2018, Dr. Li was an assistant professor at Ohio State University Department of Biomedical Informatics. He received his Ph.D. in applied mathematics in Beijing University and completed his postdoc training at Harvard Medical School in computational biology.

About the Seminar Series

The seminar is open to the public and registration is required each month. Individuals who need interpreting services and/or other reasonable accommodations to participate in this event should contact Allison Hurst at 301-670-4990. Requests should be made at least five days in advance of the event.

The National Institutes of Health (NIH) Office of Data Science Strategy hosts this seminar series to highlight examples of data sharing and reuse on the second Friday of each month at noon ET. The monthly series highlights researchers who have taken existing data and found clever ways to reuse the data or generate new findings. A different NIH institute or center will also share its data science activities each month.