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中科院計算生物學重點實驗室學術報告:Deep learning for next generation genome editing and genome interpretation

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時間:2019-05-27  來源:文本大小:【 |  | 】  【打印

Title: Deep learning for next generation genome editing and genome interpretation

Speaker : James Zou

           Assistant Professor,Stanford University

Time : 09:30-11:30 , May 28(Tuesday)

Venue : Room 315, SIBS Main Building, Yueyang Road 320

Host : Prof. Sijia Wang

       CAS-MPG Partner Institute for Computational Biology   

         



Abstract : I will discuss recent developments in deep learning and demonstrate how it enables powerful new approaches to genomics and biomedical data science. I will illustrate these advances with three recent projects in my group applying neural networks: 1) to improve the design and safety of CRISPR; 2) to capture nonlinear effects in polygenic risk score; and 3) to connect tissue imaging with spatial transcriptomics.



Bio : James Zou is an assistant professor of Biomedical Data Science, CS and EE at Stanford University. He is also an inaugural Chan-Zuckerberg Investigator and is the faculty director of the Stanford AI for Health program. His group develops state-of-the-art machine learning algorithms motivated by biomedical and health applications. His research have been published in Nature, Cell, PNAS, Nature Methods, and have been recognized with several best paper awards at RECOMB, top AI conferences as well as the Google Faculty Award.

 

All are welcome !

 

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