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清华大学材料科学与工程研究院《材料科学论坛》:机器学习辅助合金理性设计
报告题目:
Single cell molecular profiling with Qdots
 报告人:
Dr. Xiaohu Gao
Associate Professor
Department of Bioengineering
University of Washington, Seattle
报告时间:
2016-07-05 15:00
报告地点:
何添楼406会议室
主办单位:
化学系何彦课题组
  简介:

Biography:
Prof. Xiaohu Gao received his Ph.D. degree in bioanalytical chemistry from Indiana University, Bloomington in 2004, and his postdoctoral training from the Department of Biomedical Engineering at Georgia Tech and Emory University. He became a faculty member in the Department of Bioengineering and the Center for Nanotechnology at the University of Washington, Seattle in 2005. His research program is focused on biomedical nanotechnology, biomolecular engineering, molecular imaging, and targeted drug delivery. He is a recipient of the NSF CAREER Award, and has been a member of the American Chemical Society (ACS) and Biomedical Engineering Society (BMES) since 2003. He is an elected fellow of the American Institute for Medical and Biological Engineering (AIBME). He has published 75 peer reviewed articles with a total citation > 10,000 according to Web-of-Science.

Abstract:

In-depth understanding of the nature of cell physiology and ability to diagnose and control the progression of pathological processes heavily rely on untangling the complexity of intracellular molecular mechanisms and pathways. To achieve this goal, comprehensive molecular profiling of individual cells within the context of their natural tissue or cell culture microenvironment is required. Neither the conventional techniques such as immunohistochemistry nor the more advanced nanoparticle-based methods and mass spectrometry have been able to address this task up to date. Here, I present recent development of a highly multiplexed in situ imaging technology, potentially capable of creating molecular profiles consisting of 10s-100s biomarkers for single cells. This comprehensive molecular profiling technology is expected to open new opportunities in molecular diagnosis, systems biology, gene expression studies, and signaling pathway analysis.

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