Liangliang (Lyons) Zhang, PhD

Dr. Zhang’s laboratory develops statistical methodology centered on Bayesian analysis and high-dimensional modeling for complex biomedical data. The lab’s primary omics research areas include the microbiome, single-cell data, spatial and three-dimensional omics, and multi-omics integration. These methodological developments are motivated by studies of cancer, Alzheimer’s disease, HIV, chronic kidney disease, stroke, and other conditions investigated through interdisciplinary collaborations. Across these applications, the lab focuses on rigorous association studies and the identification of reproducible, biologically meaningful biomarkers that can advance disease understanding, risk prediction, and precision medicine.

Dr. Zhang is the principal investigator of an NIH/NIGMS R01, “Structure-Enhanced Statistical and Machine Learning Methods for Spatial Transcriptomics Cell Type Deconvolution and its Applications” (R01GM169393). This research develops new approaches that integrate spatial organization, gene-expression dependence, and single-cell reference information to improve the accuracy and interpretability of cell-type deconvolution in spatial transcriptomics.

His broader methodological research addresses compositionality, zero inflation, spatial and phylogenetic dependence, high dimensionality, multimodal integration, microbial contamination, and uncertainty in biomedical data. These methods support cell-type deconvolution, biomarker discovery, mediation analysis, treatment-response prediction, and knowledge-guided AI. His group develops statistical methods and accessible software for microbiome data, single-cell and spatial omics, proteomics, genomics, neuroimaging, and other high-dimensional biomedical applications.

Dr. Zhang’s collaborative research spans cancer and immunotherapy, Alzheimer’s disease and the gut–brain axis, HIV and oral inflammation, chronic kidney and cardiovascular disease, and neuroengineering. He works closely with clinicians, laboratory scientists, engineers, and computational researchers across Case Western Reserve University, University Hospitals, Cleveland Clinic, MetroHealth, and collaborating institutions nationwide.

Dr. Zhang also provides biostatistical leadership and scientific service across several interdisciplinary centers. He contributes as a Co-Investigator in the Cleveland Alzheimer’s Disease Research Center Data Management and Statistics Core, the Cleveland Digestive Diseases Research Core Center, and the Rustbelt Center for AIDS Research Systems Biology and Biostatistics Core. He is also affiliated with the Case Comprehensive Cancer Center’s Immune Oncology Program and the CWRU Center for Imaging Research and serves as a biostatistician for the Cleveland Functional Electrical Stimulation Center.

His research has produced statistical and bioinformatics tools including ZIMMA, a Bayesian framework for zero-inflated microbiome mediation analysis, and ggpicrust2, an open-source platform for microbiome functional analysis and visualization. His work has appeared in journals including The Annals of Applied Statistics, Biometrics, Briefings in Bioinformatics, Bioinformatics, Cell, Nature Communications, Cancer, iScience, and the Electronic Journal of Statistics.