6-22FromtheHumanMicrobiomeProjecttotheEarthMicrobiomeProject:LinkingMicrobesAcrossthePlanet

发布时间 :2016-06-20  阅读次数 :1150

报告题目1:From the Human Microbiome Project to the Earth Microbiome Project:  Linking Microbes Across the Planet

报  告 人:Prof. Rob Knight

Departments of Pediatrics and Computer Science & Engineering,  University of California at San Diego

 

报告题目2:Microbiome Signatures of Human Diseases

报  告 人:Dr.  Zhenjiang XU  (徐振江博士)

Departments of Pediatrics and Computer Science & Engineering,  University of California at San Diego

 

报告时间:6月22日上午9:30-11:30

报告地点:闵行校区生物药学楼800号树华多功能厅

联  系 人:张梦晖 13370259748

上海交通大学生命科学技术学院

微生物代谢国家重点实验室

上海市微生物学会

Rob Knight 简介:

Rob Knight is a Professor in the Department of Pediatrics, with an additional appointment in the Department of Computer Science, at the University of California San Diego. He was chosen as one of 50 HHMI Early Career Scientists in 2009, is a Senior Editor at the ISME Journal, a member of the Steering Committee of the Earth Microbiome Project, and a co-founder of the American Gut Project.

The Knight Lab uses and develops state-of-the-art computational and experimental techniques to ask fundamental questions about the evolution of the composition of biomolecules, genomes, and communities in different ecosystems, including the complex microbial ecosystems of the human body. We subscribe to an open-access scientific model, providing free, open-source software tools and making all protocols and data publicly available in order to increase general interest in and understanding of microbial ecology, and to further public involvement in scientific endeavors more generally.(Rob Knight’ Lab)

 

Zhenjiang (Zech) Xu,  Post-doctoral research associate

Microbiota has tremendous impacts on environment and host health and can be engineered for the better. My interests are mainly centered around linking microbiota composition and function to host phenotypes or environmental factors. I have been working on miscellaneous projects using microbiome as biomarkers for forensics, disease diagnostics and prognostics with statistical and machine learning techniques. Towards that goal, I am also developing new computational tools (e.g. micronota) to improve our understanding of microbial composition and their function.

 

 

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