Analysis of single cells allows a complete understanding of the heterogeneity that is present in cell behavior and function. Current single-cell analysis methods provide high-throughput information about labeled biomolecules within cells, but often cannot follow the dynamic processes occurring in signaling pathways. New microfluidic methods have separately allowed assays of fast timescale responses or creation of uniform environments to study cell behavior in a more quantitative manner. This book focuses on microfluidic hydrodynamic trapping techniques that aid in both fast timescale measurements and uniform environmental control in a single platform. Example applications for fast timescale analysis of pore-forming toxin insertion into membranes and assays of single-cell enzyme content will be presented. The book would be of interest to analytical chemists, engineers, and biologists developing platforms to study single-cell behavior. Also, biologists looking for tools to study cells of interest with statistical accuracy would find the book most helpful.
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Analysis of single cells allows a complete understanding of the heterogeneity that is present in cell behavior and function. Current single-cell analysis methods provide high-throughput information about labeled biomolecules within cells, but often cannot follow the dynamic processes occurring in signaling pathways. New microfluidic methods have separately allowed assays of fast timescale responses or creation of uniform environments to study cell behavior in a more quantitative manner. This book focuses on microfluidic hydrodynamic trapping techniques that aid in both fast timescale measurements and uniform environmental control in a single platform. Example applications for fast timescale analysis of pore-forming toxin insertion into membranes and assays of single-cell enzyme content will be presented. The book would be of interest to analytical chemists, engineers, and biologists developing platforms to study single-cell behavior. Also, biologists looking for tools to study cells of interest with statistical accuracy would find the book most helpful.
Dino Di Carlo is an Assistant Professor of Bioengineering at UCLA. He received his B.S. and Ph.D. in Bioengineering from UC Berkeley and San Francisco. He then conducted postdoctoral studies at Harvard Medical School and MGH. His research focuses on miniaturization technologies for advanced diagnostic and automated single cell analysis systems.
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