{"319231":{"#nid":"319231","#data":{"type":"event","title":"PhD Proposal Presentation by James Wade","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EJames Wade\u003C\/strong\u003E\u003Cbr \/\u003EPhD Proposal Presentation\u003Cbr \/\u003EDate: Thursday, September 4th, 2014\u003Cbr \/\u003ETime: 9 AM\u003Cbr \/\u003ELocation: IBB 1128\u003C\/p\u003E\u003Cp\u003EAdvisors:\u003Cbr \/\u003EEberhard Voit, PhD (GT-BME)\u003Cbr \/\u003EBarbara Boyan, PhD (Virginia Commonwealth University)\u003C\/p\u003E\u003Cp\u003ECommittee:\u003Cbr \/\u003EBernd Bodenmiller, PhD (University of Zurich)\u003Cbr \/\u003EMelissa Kemp, PhD (GT-BME)\u003Cbr \/\u003EJohn McDonald, PhD (GT-Biology)\u003Cbr \/\u003EPeng Qiu, PhD (GT-BME)\u003C\/p\u003E\u003Cp\u003ETitle:\u003Cbr \/\u003E\u003Cstrong\u003EComputational Modeling and Analysis of Single-cell Signaling Dynamics in Heterogeneous Cell Populations\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAbstract:\u003Cbr \/\u003ETumors and tissues represent heterogeneous cell populations. This heterogeneity may be due to non-genetic variability in cell state, which is determined by factors such as stochastic gene expres- sion or local differences in microenvironment. The cell state affects cellular signaling responses to a given set of inputs. Intracellularly, signal transduction is determined by a complex network of biochemical reactions that can exhibit complex nonlinear dynamics. The goal of this work is to computationally analyze signaling dynamics at the single-cell level in heterogeneous cell popu- lations. Generally, experimental studies of single-cell signaling are limited by the choice between experimental methods that can either measure the state of a few molecules in the same cells con- tinuously, or time courses of many molecules from separate cells. We propose to bridge this gap with a novel computational methodology that allows us to model and analyze single-cell signaling dynamics. The innovation of this method will be its ability to predict single-cell trajectories based on time course experiments of different cells. We will apply our method to the investigation of intracellular signaling in heterogeneous B cell and breast cancer cell populations, using data from mass cytometry (CyTOF) experiments. The computational analysis is expected to have the capac- ity of predicting novel therapeutic targets as a function of the initial cell state. These predictive results will be tested with targeted CyTOF experiments. We believe this work will significantly increase our understanding of signaling at the single-cell level.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Computational Modeling and Analysis of Single-cell Signaling Dynamics in Heterogeneous Cell Populations"}],"uid":"28077","created_gmt":"2014-08-26 14:05:56","changed_gmt":"2016-10-08 02:08:56","author":"Danielle Ramirez","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2014-09-04T10:00:00-04:00","event_time_end":"2014-09-04T12:00:00-04:00","event_time_end_last":"2014-09-04T12:00:00-04:00","gmt_time_start":"2014-09-04 14:00:00","gmt_time_end":"2014-09-04 16:00:00","gmt_time_end_last":"2014-09-04 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"1612","name":"BME"},{"id":"4407","name":"Graduate Student"},{"id":"913","name":"PhD"},{"id":"5603","name":"thesis"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}