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ZHANG, Zemin
Title:
Professor
Office Address: Integrated Science Research Center,Peking University, No.5 Yiheyuan Road, Haidian District,Beijing, P.R.China 100871
Lab Address: Integrated Science Research Center,Peking University, No.5 Yiheyuan Road, Haidian District,Beijing, P.R.China 100871
Lab Homepage: http://cancer-pku.cn/
Resume
Biography
Dr. Zhang obtained his Bachler degree in Genetics from Nankai University, and PhD in Biochemistry and Molecular Biology from Penn State University. He received additional training in Information Technology from UC Berkeley and postdoctoral trainings in Laboratory Medicine from UC San Francisco.

Prior to joining Peking University, Dr. Zhang spent over 16 years at Genentech/Roche, leading the cancer genomics and bioinformatics group to discover anticancer targets and biomarkers using new technologies such as machine learning and high throughput sequencing. He has pioneered multiple research directions in computational cancer biology and cancer genomics including the first ever whole genome tumor sequencing. He is also an inventor for 60 issued US patents, and has directly contributed to the initial finding of the molecular targets of multiple cancer therapeutic agents in clinical trials. He is on the editorial boards for journals including Cell Systems, Genome Medicine, and Cancer Informatics. He is a CUSBEA Scholar, a recipient of the 1000 Talents program, and also a Cheung Kong Scholar.
Laboratory Introduction
We aim to help advance cancer immunotherapies and targeted therapies by applying cutting-edge genomic and informatics technologies to solve important problems in cancer biology.  Our laboratory combines computational (dry) and experimental (wet) approaches to uncover both systematic trends and specific elements influencing oncogenic processes, tumor microenvironment, and drug responses. First, we use single cell sequencing technologies to delineate the detailed composition and functional status of the tumor microenvironment, in particular the landscape of the tumor infiltrating lymphocytes. We also use single cell technologies to address tumor heterogeneity and how such heterogeneity influence cancer cell evolution and drug responses.  Second, we apply advanced bioinformatics methods to the ever expanding cancer genomics “big data” to reveal cancer subtypes, driver genes, and underlying genetics basis leading to functional events such as gene fusions, allele-specific expression, and tumor-specific expression isoforms. Third, we develop innovative bioinformatics tools to analyze, integrate and visualize single cell genomics data as well as large-scale cancer genomics data so that such data can effectively serve the wide research community.