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Developing Computational and Statistical Approaches to Understand Brain Disease

The Human Neurobiology Laboratory develops and applies quantitative approaches that transform complex human brain data into biologically and clinically meaningful insights. By integrating single-cell and spatial transcriptomic and epigenomic data with proteomics, genomics, neuroimaging, neuropathology, and detailed clinical information, the lab examines brain biology across multiple scales: from molecular pathways within individual cell types to the organization of entire brain regions. Using network analysis, predictive modeling, spatial mapping, and cross-modal data integration, the lab identifies coordinated biological programs associated with depression, suicide, resilience, epilepsy, and treatment response. These approaches help distinguish disease-related molecular changes from differences in cellular composition and brain structure, connect laboratory findings with clinical characteristics, and reveal biomarkers and candidate therapeutic targets. Ultimately, this work seeks to translate the complexity of the human brain into more precise strategies for understanding, preventing, and treating psychiatric and neurological disorders.

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