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dc.contributor.advisorMark Bathe.en_US
dc.contributor.authorGuo, Syuan-Mingen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Chemistry.en_US
dc.date.accessioned2016-07-18T20:03:14Z
dc.date.available2016-07-18T20:03:14Z
dc.date.copyright2015en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/103709
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, February 2016.en_US
dc.descriptionCataloged from PDF version of thesis. "February 2016."en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractFluorescence fluctuation spectroscopy and microscopy have been powerful tools for studying molecular organization and dynamics in cells. Fluorescence Correlation Spectroscopy (FCS) has been widely applied to probing molecular dynamics in live cells with single molecule sensitivity and the ability to resolve local molecular concentrations, aggregation states, and transport mechanisms. Despite the broad utility of FCS, interpretation of cellular FCS data is often confounded by the heterogeneity in the underlying biological process and the low signal-to-noise ratio. Systematic data evaluation and interpretation become even more challenging for imaging FCS, where hundreds to thousands of FCS curves are generated in a single measurement. This thesis presents an objective Bayesian inference procedure for testing multiple competing FCS models. Bayesian inference determines model probabilities by considering the probability distributions over the full range of parameter values, thereby naturally penalizes model complexity and prevents over-fitting. We applied this procedure to imaging FCS data in order to resolve hIAPP-induced microdomain spatial organization and temporal dynamics in the cell membrane. Our analysis resolved the temporal evolution of multiple diffusing species in the spatially heterogeneous cell membrane, lending support to the "carpet model" for the association mode of hIAPP aggregates with the plasma membrane. Finally, we presented a fluctuation-based microscopy approach, Points Accumulation for Imaging in Nanoscale Topography (PAINT), that enables highly multiplexed super-resolution imaging of synaptic proteins. We employed DNA-PAINT to resolve nano-scale organization of seven targets simultaneously including synaptic proteins and cytoskeletal markers. These approaches demonstrated the broad applicability of fluorescence fluctuation spectroscopy and microscopy in resolving molecular dynamics and organization in cells.en_US
dc.description.statementofresponsibilityby Syuan-Ming Guo.en_US
dc.format.extent139 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectChemistry.en_US
dc.titleFluorescence fluctuation spectroscopy and microscopy : application to cellular molecular dynamics and organizationen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistry
dc.identifier.oclc953261914en_US


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