Haiyan Huang

Photo of Haiyan Huang

Haiyan Huang

Professor and Chair
Office / Location
317 Evans Hall
Research Expertise and Interests

high dimensional and integrative genomic data analysis, network modeling, hierarchical multi-label classification, translational bioinformatics

My research areas are in Computational Biology and Applied Statistics. Particularly, I am interested in solving practical problems in emerging bio data-intensive systems, and in understanding and developing theoretical principles of the practical methods. My current focuses are: 1) develop statistical methods that provide a consistent formulation between the statistical modeling and the biological nature of data, 2) understand and solve the problem of unreliable estimates in analyzing high dimensional structured data, and 3) tackle the challenges posed by the high level of noise and the lack of reproducibility in the datasets from different resources.

Select Publications


  1. Wang YXR, Jiang K, Feldman LJ, Bickel PJ, Huang H* (2015).g Inferring Gene-Gene Interactions and Functional Modules Using Sparse Canonical Correlation Analysis. Annals of Applied Statistics. 9(1) 300-323. *corresponding author
  2. Wang YXR, Waterman MS*, Huang H* (2014). Gene Coexpression Measures in Large Heterogeneous Samples Using Count Statistics. Proc Natl Acad Sci. USA. 111(46):16371-6. *co-corresponding authors
  3. Li JJ, Huang H*, Bickel PJ*, Brenner S* (2014). Comparison of D. Melanogaster and C. Elegans Developmental Stages, Tissues, and Cells by modENCODE RNA-seq Data. Genome Research. 24: 1084-1101. g*co-corresponding authors
  4. Jiang CR, Liu CC, Zhou XJ, Huang H* (2014). Optimal Ranking in Multi-label Classification Using Local Precision Rates. Statistica Sinica. g24: 1547-1570. *corresponding author
  5. Kim K, Teng S, Jiang K, Feldman L, Huang H* (2012). Using biologically interrelated experiments to identify pathway genes in arabidopsis. Bioinformatics. 28(6), 815-822. *corresponding author
  6. Li JJ, Jiang CR, Brown BJ, Huang H*, Bickel PJ* (2011). Sparse Linear Modeling of RNA-seq Data for Isoform Discovery and Abundance Estimation. Proc Natl Acad Sci. USA. 108 (50) 19867-19872. *co-corresponding authors
  7. Li Q, Brown JB, Huang H, Bickel PJ. (2011). Measuring Reproducibility of High-throughput Experiments. Annals of Applied Statistics. 5(3), 1752-1779.
  8. Huang H*, Liu C, Zhou XJ* (2010). Bayesian Approach to Transforming Public Gene Expression Repositories into Disease Diagnosis Databases. Proc Natl Acad Sci. USA. 107 (15) 6823-6828. *co-corresponding authors
  9. Bickel PJ, Boley N, Brown JB, Huang H, Zhang NR (2010). Subsampling Methods for Genomic Inference. Annals of Applied Statistics. 4(4) 1660-1697.
  10. Bickel P, Brown B, Huang H, Li Q (2009). An overview of recent developments in genomics and associated statistical methods. Philosophical Transactions of the Royal Society A 367, 4313-4337.
  11. Teng S, Huang H (2009). A statistical framework to infer functional gene associations from multiple biologically interrelated microarray experiments. Journal of the American Statistical Association, June 2009, Vol. 104, No. 486.