6-22FromtheHumanMicrobiomeProjecttotheEarthMicrobiomeProject:LinkingMicrobesAcrossthePlanet
發布時間 :2016-06-20  閱讀次數 :3603

報告題目1:From the Human Microbiome Project to the Earth Microbiome Project:  Linking Microbes Across the Planet

報  告 人:Prof. Rob Knight

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

 

報告題目2:Microbiome Signatures of Human Diseases

報  告 人ℹ️:Dr.  Zhenjiang XU  (徐振江博士)

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

 

報告時間👃🏽:6月22日上午9:30-11:30

報告地點🧑🏻‍🎤🙋🏽‍♀️:閔行校區生物藥學樓800號樹華多功能廳

聯  系 人👨🏼‍🚀:張夢暉 13370259748

EON体育4平台

微生物代謝國家重點實驗室

上海市微生物學會

Rob Knight 簡介:

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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