时间：2022/06/28 09:30开始

腾讯会议：958-220-305

报告题目：Linking brain-wide gene expression and neuroimaging data

摘要： The availability of brain-wide gene expression atlases, such as Allen Brain Atlas, has made it possible to connect spatial expression patterns of thousands of genes to different kinds of imaging-derived phenotypes. A growing body of evidence shows the close relationship between gene expression and diverse brain structure and function properties. These analyses can help gain insights into the transcriptional correlate of the neuroimaging phenotypes in health and disease. In this talk, I will briefly introduce the transcriptomic datasets available and review the workflows for relating transcriptomes to neuroimaging data. I will also introduce the Brain Annotation Toolbox (BAT), which we developed to provide functional/genetic annotations for the results of neuroimaging studies.

报告人简介： 刘曌雯，美国麻省总医院/哈佛医学院博士后。博士为西安电子科技大学和复旦大学类脑人工智能与技术研究院联合培养，主要研究方向为融合多组学数据、电子病历和多模态脑影像数据的算法开发和应用。现在，目前主要致力于开发新的多模态数据挖掘方法，帮助探索精神疾病的遗传和神经基础。