Kun Liang

Research Associate
Department of Statistics
Department of Biostatistics and Medical Informatics
University of Wisconsin-Madison


Ph.D Department of Statistics, Iowa State University
M.S. and B.E. Department of Automation, Tsinghua University, P. R. China


Multiple testing
Statistical analysis of genomic data
Bayesian statistics
Applications of Markov chain model
Markov chain Monte Carlo


  • Liang, K. and Nettleton, D., Adaptive and dynamic adaptive procedures for false discovery rate control and estimation, Journal of the Royal Statistical Society: Series B. In press.
  • Liang, K. and Keles, S., Detecting differential binding of transcription factors with ChIP-seq, Bioinformatics. In press. Software: DBChIP
  • Chung, D., Kuan, P.F., Li, B., Sanalkumar, R., Liang, K., Bresnick, E., Dewey, C. and Keles, S. (2011), Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-seq data, PLoS Computational Biology, 7(7): e1002111.
  • Liang, K. and Nettleton, D. (2010), A hidden Markov model approach to testing multiple hypotheses on a tree-transformed Gene Ontology graph, Journal of the American Statistical Association, 105, 1444-1454.
  • Vogel, D.L., Werner-Wilson, R.J., Liang, K., Cutrona, C.E., Seeman, J.C. and Hackler, A.H. (2008), The relationship of physiological arousal with demand and withdraw behavior: Examining the accuracy of the escape-conditioning hypothesis, Sex Role, 59, 871-879.
  • Liang, K. and Keles, S., Normalization of ChIP-seq data with control. Submitted. Technical report
  • Contact

    kliang AT stat.wisc.edu