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Brittany N Lasseigne
Summary
Brittany N. Lasseigne, PhD is an Assistant Professor of Cell, Developmental and Integrative Biology at The University of Alabama at Birmingham School of Medicine. She trained in Biotechnology, Science, and Engineering at Mississippi State University (B.S.) and the University of Alabama in Huntsville (Ph.D.) and completed a postdoctoral fellowship in genetics and genomics at the HudsonAlpha Institute for Biotechnology.
Her lab develops and applies genomic- and data-driven strategies (including single-cell and long-read sequencing) to discover biological signatures that might be used to improve patient care and provide insight into the cellular and molecular processes contributing to disease, especially for diseases impacting the brain and/or kidney. Their recent work includes prioritizing drug repurposing candidates for cancers and polycystic kidney disease, evaluating preclinical models and cross-species transcriptomic signatures to improve disease modeling, and applying single-cell and long-read technologies to neurological disease tissues to understand the role that context plays in disease etiology, progression, and treatment.
The Lasseigne Lab is currently focused on integrating genomics data, functional annotations, and patient information with machine learning and regulatory network approaches across diseases that impact the brain or kidney to discover novel mechanisms in disease etiology and progression, identify genome-driven therapeutic targets and opportunities for drug repositioning and repurposing, determine clinically-relevant biomarkers, and understand how cellular context contributes to these diseases. Collectively, these distinct projects all apply genetics and genomics to human diseases and build tools to accelerate future research. Their lab also develops data science software and analytical pipelines that are open-source, well-documented, and hosted by third-party code distributors, critical for facilitating reproducibility and enabling the research community to use the methods they develop.
Bioinformatics Computational Biology Data Mining & Machine Learning Genomics Nephrology Neuroscience Oncology Pharmacology