Yunguan Wang, PhD

Biography

I am a computational biologist by training and currently an Assistant Professor in the Division of Pediatric Gastroenterology, Hepatology and Nutrition at Cincinnati Children's Hospital Medical Center. My primary research objective is to advance our understanding of autoimmune liver disease pathogenesis through the modeling of high-dimensional data, particularly genomics data. I have focused on single-cell genomics and spatial transcriptomics, utilizing both public and in-house profiling data to explore biological processes in health and disease. In recent years, my research has concentrated on developing computational tools for spatially resolved transcriptomics (SRT) data, enabling robust predictions of cell-cell communication (CCC) between cells. For instance, I developed a mathematical model called Sprod, which reduces noise in gene expression from SRT data by leveraging latent space embedding and graph learning of matched location and image information from cells (Nature Methods, 2022). Additionally, I created the Spacia algorithm, which prioritizes single-cell-level CCCs from SRT data by jointly modeling spatial proximity between cells and signal/response gene associations (Nature Methods, 2024). To support tissue-level interpretation of CCC patterns, I also developed a deep-learning-based pipeline, the Tissue Positioning System (TPS), which identifies and segments tissue structures from images (EbioMedicine, 2023).