Yunguan Wang, PhD

Member, Division of Pediatric Gastroenterology, Hepatology and Nutrition
Assistant Professor, UC Department of Pediatrics

yunguan.wang@cchmc.org

About

Biography

My research areas include cellular mechanisms in healthy and diseased livers and method development for single-cell and spatial transcriptomic data analysis.

I like all kinds of mysteries, and among them, I am most intrigued by the balance between the robustness and adaptivity of biological systems. Why did some organisms evolve and adapt to environmental change while others didn’t? How do perturbations breach the robustness of biological processes and potentially lead to diseases? Questions like this have always fascinated me.

My current research aims to understand how cells communicate with each other and how these interactions guide normal biological processes and direct development. Conversely, how do disrupted interaction patterns contribute to disease?

My past research work includes a tissue positional system for automatically discovering and annotating tissue patterns from liver images using deep learning and the state-of-the-art algorithm (Sprod) for noise reduction in spatial transcriptomic data using both image information and spatial proximity.

I've been a researcher in biomedical informatics for over five years and began working at Cincinnati Children's in 2023. My research has been published in journals such as Science, Cell, Nature Methods and Nature Cancer.

Services and Specialties

Gastroenterology

Interests

Bioinformatics; spatial transcriptomics; single-cell transcriptomics

Research Areas

Gastroenterology Hepatology and Nutrition

Publications

Loss of SYNCRIP unleashes APOBEC-driven mutagenesis, tumor heterogeneity, and AR-targeted therapy resistance in prostate cancer. Li, X; Wang, Y; Deng, S; Zhu, G; Wang, C; Johnson, NA; Zhang, Z; Tirado, CR; Xu, Y; Metang, LA; et al. Cancer Cell. 2023; 41:1427-1449.e12.

IGFBP2 expressing midlobular hepatocytes preferentially contribute to liver homeostasis and regeneration. Lin, Y; Wei, Y; Zeng, Q; Wang, Y; Pagani, CA; Li, L; Zhu, M; Wang, Z; Hsieh, M; Corbitt, N; et al. Cell Stem Cell. 2023; 30:665-676.e4.

Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease. Wang, Z; Zhu, S; Jia, Y; Wang, Y; Kubota, N; Fujiwara, N; Gordillo, R; Lewis, C; Zhu, M; Sharma, T; et al. Cell. 2023; 186:1968-1984.e20.

Netie: inferring the evolution of neoantigen-T cell interactions in tumors. Lu, T; Park, S; Han, Y; Wang, Y; Hubert, SM; Futreal, PA; Wistuba, I; Heymach, JV; Reuben, A; Zhang, J; et al. Nature Methods. 2022; 19:1480-1489.

Arid1a loss potentiates pancreatic β-cell regeneration through activation of EGF signaling. Celen, C; Chuang, J; Shen, S; Li, L; Maggiore, G; Jia, Y; Luo, X; Moore, A; Wang, Y; Otto, JE; et al. Cell Reports. 2022; 41:111581.

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses. Gross, SM; Dane, MA; Smith, RL; Devlin, KL; McLean, IC; Derrick, DS; Mills, CE; Subramanian, K; London, AB; Torre, D; et al. Communications Biology. 2022; 5:1066.

Ectopic JAK-STAT activation enables the transition to a stem-like and multilineage state conferring AR-targeted therapy resistance. Deng, S; Wang, C; Wang, Y; Xu, Y; Li, X; Johnson, NA; Mukherji, A; Lo, U; Xu, L; Gonzalez, J; et al. 2022; 3:1071-1087.

Sprod for de-noising spatially resolved transcriptomics data based on position and image information. Wang, Y; Song, B; Wang, S; Chen, M; Xie, Y; Xiao, G; Wang, L; Wang, T. Nature Methods. 2022; 19:950-958.

Deep learning-based prediction of the T cell receptor-antigen binding specificity. Lu, T; Zhang, Z; Zhu, J; Wang, Y; Jiang, P; Xiao, X; Bernatchez, C; Heymach, JV; Gibbons, DL; Wang, J; et al. 2021; 3:864-875.

Spatial molecular profiling: platforms, applications and analysis tools. Zhang, M; Sheffield, T; Zhan, X; Li, Q; Yang, DM; Wang, Y; Wang, S; Xie, Y; Wang, T; Xiao, G. Briefings in Bioinformatics. 2021; 22:bbaa145.