Academic Report of Shanghai Fishery Peak Discipline

The release date:2017-03-30view:246Set

Lecturer: Doctor Ye Kai, Professor of Xi'an Jiaotong University

Title: Application of Genome Informatics in Medical Treatment

Lecturer: Doctor Yang Xiaofei, Associate Professor of Xi’an Jiaotong University

Title: Comparative pan-cancer DNA methylation analysis reveals cancer common and specific patterns

Time: 15:00-17:00, April 5, 2017 (Wednesday)

Address: Conference Room A211, the College of Fisheries and Life Science

About the lecturer:

Ye Kai, Professor of Xi’an Jiaotong University, graduated with Bachelor and Master Degrees from Wuhan University, and obtained a Ph.D. Degree in Bioinformatics from the University of Leiden of Netherlands in 2008. From July of 2008 to June of 2009, he served as a postdoctoral researcher at EMBL-European Bioinformatics Institute; from July of 2009 to November of 2012, he served as Assistant Professor at the Medical Center of the University of Leiden of Netherlands; from November of 2012 to January of 2016, he was Assistant Professor at the Institute for Genomic Research of the School of Medicine of Washington University in St Louis. Professor Ye Kai is engaged in research work in the fields of bioinformatics and genomics on a long-term basis, and was one of the first group of researchers touching upon the second-generation high throughput sequencing technique and data; he also participated in the “1,000 Genomes Project”, The Cancer Genome Atlas (TCGA) and many other major international scientific projects with fruitful achievements. He has published 52 papers on Nature, Nature Medicine, Genome Research and many other internationally-famous academic journals, and the sum of the times cited has reached about 13,000.

Yang Xiaofei, Associate Professor of Xi’an Jiaotong University, is a member of Professor Ye Kai’s team, and his main research directions include data mining and bioinformatics. He is mainly engaged in researches on biological big data analysis, including long non-coding RNA and DNA methylation pathogenesis pattern mining algorithms.

We sincerely expect the presence of our faculties and students!

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