{"569621":{"#nid":"569621","#data":{"type":"event","title":"PhD Defense by Charles Zhao","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ECharles Zhao\u0026nbsp;\u003Cbr \/\u003E \u003C\/strong\u003EBME Ph.D.\u0026nbsp;Defense\u0026nbsp;Presentation\u003Cbr \/\u003E \u003Cstrong\u003EDate:\u0026nbsp;\u003C\/strong\u003EThursday, September 8\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETime:\u003C\/strong\u003E\u0026nbsp;1 PM\u003Cbr \/\u003E \u003Cstrong\u003ELocation:\u0026nbsp;\u003C\/strong\u003EGeorgia Tech Engineered Biosystems Building, Children\u0027s Healthcare of Atlanta Seminar Room (1st floor)\u003Cbr \/\u003E \u003Cstrong\u003E\u0026nbsp;\u003Cbr \/\u003E Advisors:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EHang Lu,\u0026nbsp;PhD\u0026nbsp;(Georgia Institute of Technology)\u003Cbr \/\u003E \u003Cstrong\u003ECommittee Members:\u003Cbr \/\u003E \u003C\/strong\u003ERobert Butera,\u0026nbsp;PhD\u0026nbsp;(Georgia Institute of Technology)\u003C\/p\u003E\u003Cp\u003EPatrick Mcgrath,\u0026nbsp;PhD\u0026nbsp;(Georgia Institute of Technology)\u003Cbr \/\u003E Chris Rozell, PhD (Georgia Institute of Technology)\u003Cbr \/\u003E Kang Shen,\u0026nbsp;PhD\u0026nbsp;(Stanford University)\u003Cbr \/\u003E \u003Cstrong\u003E\u003Cbr \/\u003E Title:\u003Cbr \/\u003E \u003C\/strong\u003E\u0022Quantitative Analysis, Image Processing, and High-throughput Techniques for Neural Imaging in\u0026nbsp;\u003Cem\u003EC. elegans\u003C\/em\u003E.\u0022\u003Cbr \/\u003E \u003Cstrong\u003E\u003Cbr \/\u003E Abstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe use of image processing and quantitative feature extraction in the biological sciences has become increasingly prominent in recent years, as advances in technique allow the collection of increasing amount of high-quality images. With high-volume, quantitative phenotypic descriptors, it becomes possible to elucidate previously unseen aspects of the genotype-phenotype relationship, making the efficient parameterization and statistical analysis of large numbers of images more important than ever.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EBy developing and applying image processing techniques\u0026nbsp;in the model organism\u0026nbsp;\u003Cem\u003EC. elegans\u003C\/em\u003E, we explore the relationship between synapse-affecting genes and synaptic morphology\u003Cem\u003E,\u003C\/em\u003E\u0026nbsp;as well as the tracking of the real-time functional\u0026nbsp;activity of neurons throughout the head ganglion on a large scale (\u0022whole brain\u0022 imaging), seeking to develop novel methodologies of value to the whole community. By expanding\u0026nbsp;a pre-existing imaging and processing pipeline to dimmer and more precise synaptic markers, we\u0026nbsp;more broadly and accurately characterize the effects of already-established synaptic mutants. We then use this pipeline to perform a\u0026nbsp;novel application of Quantitative Trait Loci (QTL) analysis on fluorescently-labeled synapses, a previously-infeasible study, demonstrating quantitative genetics on a subtle, different to phenotype feature, and identifying a potential QTL affecting synaptic morphology on chromosome IV. Finally, we turn our attention to function,\u0026nbsp;examining the problem of monitoring many neurons in the head ganglion of\u0026nbsp;\u003Cem\u003EC. elegans\u003C\/em\u003E\u0026nbsp;simultaneously,\u0026nbsp;developing a segmentation, tracking, and data processing pipeline that requires no manual correction, and which can process volumetric neural videos far faster than previous manual approaches.We demonstrate this both by reproducing the manual curation of published videos, and by analyzing a large number videos taken ourselves. We expect the techniques and algorithms developed to be of broad value to researchers, providing a valuable new approach to QTL analysis in previous infeasible cases, and allowing for the first time the efficient processing of \u0022whole brain\u0022 imaging data\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E \u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Quantitative Analysis, Image Processing, and High-throughput Techniques for Neural Imaging in C. elegans"}],"uid":"27707","created_gmt":"2016-08-29 13:29:59","changed_gmt":"2016-10-08 02:19:00","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2016-09-08T14:00:00-04:00","event_time_end":"2016-09-08T16:00:00-04:00","event_time_end_last":"2016-09-08T16:00:00-04:00","gmt_time_start":"2016-09-08 18:00:00","gmt_time_end":"2016-09-08 20:00:00","gmt_time_end_last":"2016-09-08 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"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":""}}}