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Clinical and Methodological Advances in Imaging Genetics
时间:2020年12月23日 20:31 点击数:

报告人: Hongtu Zhu

报告地点:腾讯会议

报告时间:2020年12月26日星期六9:00-10:00

邀请人:郑术蓉

报告摘要:

Recently the UK Biobank study has conducted brain MRI imaging scans of over 40,000 participants. In addition, publicly available imaging genetic datasets also emerge from several other independent studies. We collected massive individual-level MRI data from different data resources, harmonized image processing procedures, and conducted the largest genetic studies so far for various neuroimaging traits from different structural and functional modalities. In this talk, we showcase novel clinical findings from our largescale analyses. We establish genetic mappings from hundreds of anatomical brain regions onto their corresponding functional connectivities, and further onto complex mental disorders, which may transverse our understanding of the disease emergence and development. We also discuss methodological challenges we have faced when processing these biobank-scale datasets and highlight opportunities to utilize the learned knowledges in downstream analyses for disease predictions and pathway analyses.

会议ID:880 882 458

本报告也是国家天元数学东北中心统计学主题的系列报告之一。

主讲人简介:

Dr. Hongtu Zhu is a tenured professor of biostatistics at University of North Carolina at Chapel Hill and DiDi Fellow and Chief Scientist of Statistics at DiDi Chuxing.He was Endowed Bao-Shan Jing Professorship in Diagnostic Imaging at MD Anderson Cancer Center. He has been an elected Fellow of American Statistical Association and Institute of Mathematical Statistics since 2011. He received an established investigator award from Cancer Prevention Research Institute of Texas in 2016 and received the INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice in 2019. He has published more than 280 papers/chapters in top journals, as well as 42 conference papers in top conferences.He has served/is serving an editorial board member of premier international journals including Statistica Sinica, JRSSB, Annals of Statistics, and Journal of American Statistical Association.

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