Zhenqiu Liu


Department of Statistics
E-mail: zhenqiu_l@rerf.or.jp


Dr. Liu is a Senior Scientist at the Department of Statistics, RERF. Before moving to RERF, he was an Associate Professor in Bioinformatics at the Department of Public Health Sciences, Pennsylvania State University. Previously, he was the Director of Bioinformatics/Associate Professor at Cedars-Sinai Medical Center from 2013-2018, and an Assistant/Associate Professor at the University of Maryland School of Medicine from 2005-2013. His research interests are in the broad areas of bioinformatics, computational medicine, and data sciences. More specifically, his research concentrates on statistical and machine learning methods for multi-omics integration and risk prediction, methods for single-cell sequencing analysis, and causal inference and biomarker identification in radio-genomics. He has extensive collaborative experience in laboratory investigations, biomarker evaluation, omics, and clinical and epidemiological studies.


Doctor of Philosophy, Operations Research (Management Science), The University of Tennessee, Knoxville, TN, USA.
Master of Science, Computer Science, The University of Tennessee, Knoxville, TN, USA.
Master of Science, Applied Math, Shandong University, Shandong Province, China
Bachelor of Engineering, Applied Geophysics, Jilin University, Jilin Province, China


Radiation Effects Research Foundation, Department of Statistics
  • 2022-

    Senior Scientist

Pennsylvania State University, College of Medicine, Hershey, Pennsylvania, USA
  • 2018-2022

    Associate Professor of Bioinformatics, Department of Public Health Sciences

Cedars-Sinai Medical Center, Los Angeles, California, USA
  • 2013-2018

    Director of Bioinformatics/Associate Professor, Samuel Oschin Comprehensive Cancer Institute

University of Maryland School of Medicine, Baltimore, Maryland, USA
  • 2010-2013

    Associate Professor, Division of Bioinformatics and Biostatistics, Department of Epidemiology and Public Health

  • 2005-2010

    Assistant Professor (tenure track), Division of Bioinformatics and Biostatistics, Department of Epidemiology and Public Health

The Ohio State University, Columbus, Ohio, USA
  • 2004-2005

    Postdoctoral Research Fellow in statistical genetics and bioinformatics, Department of Statistics

US Amy Medical Research and Material Command, Frederick, Maryland, USA
  • 2003-2004

    Postdoctoral Research Fellow, Bioinformatics Cell, Telemedicine and Advanced Technology Research Center

The University of Tennessee, Knoxville, Tennessee, USA
  • 2002-2003

    Senior Computer Programmer, Community Health Research Group

Selected publications

Liu Z. Clustering Single-Cell RNA-Seq Data with Regularized Gaussian Graphical Model. Genes (Basel). 2021 Feb 22; 12(2):311. doi: 10.3390/genes12020311.
Liu Z. Visualizing Single-Cell RNA-seq Data with Semi-supervised Principal Component Analysis. Int J Mol Sci. 2020 Aug 12; 21(16):5797. doi: 10.3390/ijms21165797.
Liu Z, Elashoff D, Piantadosi S. Sparse support vector machines with L0 approximation for ultra-high dimensional omics data. Artif Intell Med. 2019 May; 96:134-141. doi: 10.1016/j.artmed.2019.04.004.
Liu Z, Sun F, McGovern DP. Sparse Generalized Linear Model with L0 Approximation for Feature Selection and Prediction with Big Omics Data. Biodata Mining. 2017 Dec 19; 10:39. doi: 10.1186/s13040-017-0159-z.
Liu Z, Lin S, Deng N, McGovern D, Piantadosi S. Sparse inverse covariance estimation with L0 Penalty for Network Construction with Omics Data. Journal of Computational Biology. 2016 Mar; 23(3):192-202.
Liu Z, Sun F, Braun J, McGovern D, Piantadosi S. Multilevel Regularized Regression for Simultaneous Taxa Selection and Network Construction with Metagenomic Count Data. Bioinformatics. 2014 Nov 20.
Liu Z, Hsiao W, Cantarel BL, Drábek EF, Fraser-Liggett C. Sparse Distance Based Learning for Simultaneous Multiclass Classification and Feature Selection of Metagenomic Data. Bioinformatics. 2011 Oct 7.
Liu Z, Lin S, Tan M. Sparse support vector machine with Lp penalty for biomarker discovery. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB). 2010 Jan-Mar; 7(1): 100-7.
Liu Z, Tan M. ROC Based Utility function Maximization for Feature Selection and Classification with Application to High Dimensional protease Data. Biometrics. 2008 Mar 24.
Liu Z, Lin, S. Multiplies LD measure and tagging SNP selection with generalized mutual information. Genetic Epidemiology. 2005; vol.19, 4, (353-364).