Investigates gene regulatory networks in cellular processes using computational and statistical approaches.
Our laboratory investigates gene regulatory networks in cellular processes using computational and statistical approaches. We develop quantitative models and statistical learning methods for genomics. This involves analyzing "big data" from cutting-edge sequencing technologies and integrating various types of high-throughput genomic datasets. We have a particular interest in modeling genome regulation, including, but not limited to, transcription, noncoding RNA regulation and chromatin organization.
2013-Assistant Professor (affiliated), Department of Genetics and Developmental Biology, University of Connecticut School of Medicine, Farmington, CT
2013-Assistant Professor (affiliated), Department of Biomedical Engineering, University of Connecticut, Storrs, CT
2012-Assistant Professor, The Jackson Laboratory for Genomic Medicine, Farmington, CT
2013 - Eighth Annual Young Investigators, GenomeWeb
2009-2010 - Predoctoral Training Grant, California Institute for Regenerative Medicine and Stanford University
2004 - Innovation Award, Peking University
2003 -Choong Shin-Piaw Physical Science Forum Scholarship, Peking University
2002 - World’s Top 20 Certificate of Distinction, S*Star Bioinformatics Education
2002 - Diploma of Graduation with Highest Distinction, Beijing City
2002 -Diploma of Graduation with Highest Distinction, Peking University
Yuping Zhang, Zhengqing Ouyang. Joint principal trend analysis for longitudinal high-dimensional data. Biometrics. 2017.
Zhang Y, Ouyang Z, Zhao H , A statistical framework for data integration through graphical models with application to cancer genomics. Annals of Applied Statistics. 161-184, 2017.
Zhang Y, Linder MH, Shojaie A, Ouyang Z, Shen R, Baggerly KA, Baladandayuthapani V, Zhao H, Dissecting pathway disturbances using network topology and multi-platform genomics data, Statistics in Biosciences. First Online: 04 May 2017.
Zou C, Zhang Y, Ouyang Z. HSA: integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure. Genome Biology. 17:40, 2016.
Yue Wan, Kun Qu, Qiangfeng Cliff Zhang,1 Ryan A. Flynn, Ohad Manor, Zhengqing Ouyang, Jiajing Zhang, Robert C. Spitale, Michael P. Snyder, Eran Segal, and Howard Y. Chang. Landscape and variation of RNA secondary structure across the human transcriptome. Nature. 505(7485): 706–709, 2014.
Zhengqing Ouyang, Qing Zhou, and Wing Hung Wong. ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells. Proc Natl Acad Sci U S A. 106(51): 21521–21526, 2009.
Ouyang Z, Zheng GX, Chang HY. Noncoding RNA landmarks of pluripotency and reprogramming. Cell Stem Cell. 7(6): 649–650, 2010.