Dr. Zhiwu Zhang

Zhiwu Zhang

Assistant Professor of Distinguished Professorship for Statistical Genomics (Washington Grain Commission)

105 Johnson Hall
PO Box 646420
Pullman WA 99164-6420 USA
Phone (Office): 509-335-2899
Phone (Lab): 509-335-4551
Fax: 509-335-8674
Email: zhiwu.zhang@wsu.edu

Curriculum Vitae (pdf)

Zhiwu Zhang Lab Website

Google Scholar


Ph.D.     Statistical Genetics, Michigan State University, 1998
Ph.D.     Animal Breeding and Genetics, Northeast Agricultural University, China, 1991
M.S.       Animal Breeding and Genetics, Jilin Agricultural University, China, 1988
B.S.        Animal Science, Jilin Agricultural University, China, 1982


Committed to develop innovative, cutting-edge statistical methods and computing tools to advance genomic research toward the sustainability of food production and healthcare management. The focused areas are gene mapping and genomic prediction. The developed statistical methods include gBLUP (genomic Best Linear Unbiased Prediction (J. Anim. Science, 2017), compressed mixed linear model (Nature Genetics, 2010), and FarmCPU (PLoS Genetics, 2016). The released software packages include TASSEL (Bioinformatics, 2007), GAPIT (Bioinformatics, 2012 and Plant Genome 2016), and iPat (Bioinformatics, 2018). Vertical zones cover conventional statistics, Bayesian statistics, and artificial intelligent.  Horizontal scopes cover agronomy, genomics, and remote sensing.

Selected Publications

  1. Chunpeng, C. and Z. Zhang*.  2018. iPat: Intelligent Prediction and Association Tool for Genomic Research. Bioinformatics, bty015.
  2. Wang, J., Z. Zhou, Zhe Zhang, H. Li, D. Liu, Q. Zhang, P.J. Bradbury, E.S. Buckler, and Zhiwu Zhang*, 2018. Expanding the BLUP alphabet for genomic prediction adaptable to the genetic architectures of complex traits. Heredity.
  3. Liu, X., M. Huang, B. Fan, E.S. Buckler, and Z. Zhang*. 2016. Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies. PLoS Genetics. DOI: 10.1371/journal.pgen.1005767.
  4. Tang, Y., X. Liu, J. Wang, M. Li, Q. Wang, F. Tian, Z. Su, Y. Pan, D. Liu, A.E. Lipka, E.S. Buckler, and Z. Zhang*. 2016. GAPIT Version 2: An Enhanced Integrated Tool for Genomic Association and Prediction. The Plant Genome. 9(2) 1-9.
  5. Zhou, Y. , M.I. Vales, A. Wang, and Z. Zhang*. 2016. Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction. Briefings in Bioinformatics. 18(6) 1093.
  6. Wang, Q., F. Tian, Y. Pan, E.S. Buckler, and Z. Zhang*. 2014. A SUPER Powerful Method for Genome Wide Association Study. PLoS One 9:e107684.
  7. Li, M., X. Liu, P. Bradbury, J. Yu, Y-M Zhang, R.J. Todhunter, E.S. Buckler, and Zhang*. 2014. Enrichment of Statistical Power for Genomoe-wide Association Studies. BMC Biol 12:73.
  8. Yang, Y., Q. Wang, Q. Chen, R. Liao, X. Zhang, H. Yang, Y. Zheng, Zhang*, and Y. Pan*. 2014. A New Genotype Imputation Method with Tolerance to High Missing Rate and Rate Variants. PloS One 9 (6), e101025.
  9. Zhang, Z.*, Ersoz, C.Q. Lai, R.J. Todhunter, H.K. Tiwari, M.A. Gore, P.J. Bradbury, J. Yu, D.K. Arnett, J.M. Ordovas, and E.S. Buckler. 2010. Mixed Linear Model Approach Adapted for Genome-Wide Association Studies. Nature Genetics 42: 355-360.
  10. Zhang, Z.*,S. Buckler, T.M. Casstevens and P.J. Bradbury. 2009. Software Engineering the Mixed Model for Genome-wide Association Studies on Large Samples. Briefings in Bioinformatics 10(6):664-675.
  11. Zhang, Z.,J. Todhunter, E.S. Buckler, and L.D. Van Vleck*. 2007. Technical Note: Use of Marker-based Relationships with Multiple-trait Derivative-free Restricted Maximal Likelihood. J Anim Sci, 85: 881-885.
  12. Zhang, Z., P.J. Bradbury*, D.E. Kroon, T.M. Casstevens, Y. Ram-doss, and E.S. Buckler. 2007. TASSEL: Software for Association Mapping of Complex Traits in Diverse Samples. Bioinformatics 20: 2839-2840.

News Articles

NSF grant aims to use big data to improve crops

By Tina Hilding, communications director, Voiland College of Engineering and Architecture, 509-335-5095, thilding@wsu.edu

Award on Developing Non-food Grade Brassica Biofuel Feedstock Cultivars

Agency: DOE

Investigators: Jack Brown, Jim B. Davis, Aaron Esser, Kurt Schroeder, Fangming Xiao, Zhiwu Zhang

$400K grant to help solve preharvest wheat sprouting

Agency: USDA

Investigators: Arron Carter, Camille Steber, and Zhiwu Zhang

Juggling thousands of balls

By Scott A. Yates, Director of Communication at Washington Grain Commission

‘Cyber breeder’ improves wheat varieties

By Matthew Weaver at Capital Press

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