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A high content imaging-based approach for classifying cellular phenotypes.
Methods of Molecular Biology (2013)
  • Joseph J. Kim, Rutgers University
  • Sebastián L. Vega, Rowan University
  • Prabhas V. Moghe, Rutgers University
Abstract
Current methods to characterize cell–biomaterial interactions are population-based and rely on imaging or
biochemical analysis of end-point biological markers. The analysis of stem cells in cultures is further
challenged by the heterogeneous nature and divergent fates of stem cells, especially in complex, engineered
microenvironments. Here, we describe a high content imaging-based platform capable of identifying cell
subpopulations based on cell phenotype-specific morphological descriptors. This method can be utilized to
identify microenvironment-responsive morphological descriptors, which can be used to parse cells from a
heterogeneous cell population based on emergent phenotypes at the single-cell level and has been successfully
deployed to forecast long-term cell lineage fates and screen regenerative phenotype-prescriptive
biomaterials.
Disciplines
Publication Date
January 1, 2013
DOI
10.1007/7651_2013_29
Citation Information
Joseph J. Kim, Sebastián L. Vega and Prabhas V. Moghe. "A high content imaging-based approach for classifying cellular phenotypes." Methods of Molecular Biology Vol. 1052 (2013) p. 41 - 48
Available at: http://works.bepress.com/sebastian-vega/15/