AUTOMATED METHODS TO IDENTIFY PATTERNS OF FEATURES BETWEEN CELL TYPES

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Keywords: Volume data analysis, visualization and distribution collaboration Abstract: Cells, grown in a 96 well plate, are imaged using multiple modalities to identify over 108 individual physiological cellular measurements or features, including the nuclear density, cell perimeter, post-translational modifications, specific assays to calculate the percentage of cells in S-phase and mitosis [Gasparri, et al. 2004. J Biomol Screen 9:232-243], cytoplasm-nuclear translocation, characterization of cellular toxicity, and receptor internalization. The goal of this project is to develop approaches to identify patterns of features (individual physiological cellular measurements) between cell types.