Zhenqiu Liu
Affiliation
Department of Statistics
E-mail: zhenqiu_l@rerf.or.jp
E-mail: zhenqiu_l@rerf.or.jp
About
Dr. Zhenqiu Liu is a Senior Scientist in the Department of Statistics at the Radiation Effects Research Foundation (RERF). Prior to joining RERF, he served as an Associate Professor of Bioinformatics in the Department of Public Health Sciences at Pennsylvania State University. He previously held the positions of Director of Bioinformatics and Associate Professor at Cedars-Sinai Medical Center (2013–2018), and an Assistant/Associate Professor at the University of Maryland School of Medicine (2005–2013). Dr. Liu’s research focuses on bioinformatics, computational medicine, and data science, with particular emphasis on developing statistical and machine learning methods for multi-omics data integration, disease risk prediction, single-cell sequencing analysis, causal inference, and interpretable neural network (AI) models. His work integrates methodological innovation with biomedical applications to advance precision medicine and population health. He has extensive collaborative experience in laboratory research, biomarker discovery and validation, multi-omics studies, and clinical and epidemiological investigations.
Education
- 2002
- Doctor of Philosophy, Operations Research (Management Science), The University of Tennessee, Knoxville, TN, USA.
- 2002
- Master of Science, Computer Science, The University of Tennessee, Knoxville, TN, USA.
- 1989
- Master of Science, Applied Math, Shandong University, Shandong Province, China
- 1986
- Bachelor of Engineering, Applied Geophysics, Jilin University, Jilin Province, China
Experience
- Radiation Effects Research Foundation, Department of Statistics
-
- 2022-
Senior Scientist
- 2022-
- Pennsylvania State University, College of Medicine, Hershey, Pennsylvania, USA
-
- 2018-2022
Associate Professor of Bioinformatics, Department of Public Health Sciences
- 2018-2022
- Cedars-Sinai Medical Center, Los Angeles, California, USA
-
- 2013-2018
Director of Bioinformatics/Associate Professor, Samuel Oschin Comprehensive Cancer Institute
- 2014-2018
Adjunct Associate Professor, Department of Medicine, UCLA
- 2013-2018
- 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
- 2010-2013
- The Ohio State University, Columbus, Ohio, USA
-
- 2004-2005
Postdoctoral Research Fellow in statistical genetics and bioinformatics, Department of Statistics
- 2004-2005
- US Army Medical Research and Material Command, Frederick, Maryland, USA
-
- 2003-2004
Postdoctoral Research Fellow, Bioinformatics Cell, Telemedicine and Advanced Technology Research Center
- 2003-2004
- The University of Tennessee, Knoxville, Tennessee, USA
-
- 2002-2003
Senior Computer Programmer, Community Health Research Group
- 2002-2003
Selected publications
- Liu Z, Nakamizo T, Misumi M, Ono S, Shuryak I, Ullrich RL. Deep learning for incidence rate prediction and radiation risk assessment of solid tumors. Sci Rep. 2026; 16(1):10577. doi: 10.1038/s41598-026-46756-8.
- Liu Z, Cologne J, Amundson SA, Noda A. Candidate biomarkers and persistent transcriptional responses after low and high dose ionizing radiation at high dose rate. Int J Radiat Biol. 2023;99(12):1853-1864. doi: 10.1080/09553002.2023.2241897.
- 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, 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 DP, Piantadosi S. Multilevel regularized regression for simultaneous taxa selection and network construction with metagenomic count data. Bioinformatics. 2015;31(7):1067-74. doi: 10.1093/bioinformatics/btu778.
- 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;27(23):3242-9. doi: 10.1093/bioinformatics/btr547.
- 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 ; 7(1): 100-7.
- Liu Z, Tan M. ROC-based utility function maximization for feature selection and classification with applications to high-dimensional protease data. Biometrics. 2008; 64(4):1155-61. doi: 10.1111/j.1541-0420.2008.01015.x.
- Liu Z, Lin, S. Multiplies LD measure and tagging SNP selection with generalized mutual information. Genetic Epidemiology. 2005; vol.19, 4, (353-364).