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dc.contributor.authorLevsky, Jeffrey Michael
dc.date.accessioned2018-07-12T17:32:53Z
dc.date.available2018-07-12T17:32:53Z
dc.date.issued2002
dc.identifier.citationSource: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4154.;Advisors: Robert H. Singer.
dc.identifier.urihttps://yulib002.mc.yu.edu/login?url=http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:3106734
dc.identifier.urihttps://hdl.handle.net/20.500.12202/670
dc.description.abstractA key goal of biology is to relate expression of specific genes to a particular cellular phenotype. However current assays for gene expression either destroy the structural context and average expression over a population or rely on amplification steps that bias results. We hypothesized that a new approach allowing cell-level analysis of gene expression without amplification of target mRNA or disruption of the tissue would yield insight into regulation of transcription and single-cell physiology. By combining advances in computational fluorescence microscopy with multiplex probe design, we devised technology in which the expression of many genes can be visualized simultaneously inside single cells with high spatial and temporal resolution. Based on oligomer probe fluorescence in situ hybridization, the multi-spectral assay is highly automated, utilizing computer algorithms for three-dimensional image interpretation and data analysis. Detection of multiple genes responding to serum activation in individual cultured cells has revealed population diversity in repertoire of expression. We explored patterns of expression correlation in single cells and the activation kinetics of stimulated genes by allele. The technique also allowed us to map the topology of organized transcription within the nuclear architecture. Unlike previous methods, we used the nucleus as the substrate for parallel gene analysis, yielding a platform for the fusion of functional genomics and cell biology that we have termed 'cellular genomics'.
dc.publisherProQuest Dissertations & Theses
dc.subjectCellular biology.
dc.titleSingle cell gene expression profiling
dc.typeDissertation


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