K. M. McSweeney, A. B. Gussow, S. S. Bradrick, S. A. Dugger, S. Gelfman, Q. Wang, S. Petrovski, W. N. Frankel, M. J. Boland, D. B. Goldstein. (2016) Inhibition of microRNA 128 promotes excitability of cultured cortical neuronal networks. Genome Research 26 (10), 1411-1416.

A. B. Gussow, S. Petrovski , Q. Wang, A. S. Allen, and D. B. Goldstein. (2016). The Intolerance to Functional Genetic Variation of Protein Domains Predicts the Localization of Pathogenic Mutations Within Genes. Genome Biol 17 (1): 9. doi:10.1186/s13059-016-0869-4

S. Petrovski, A. B. Gussow, Q. Wang, M. Halvorsen, Y. Han, W. H. Weir, A. S. Allen and D. B. Goldstein (2015), The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity. PLoS Genet 11(9): DOI: 10.1371/journal.pgen.1005492.

H. J. Kim, L. Cox, A. F. Karr, J. P. Reiter and Q. Wang (2015), Simultaneous edit-imputation for continuous microdata. Journal of the American Statistical Association,DOI:10.1080/01621459.2015.1040881.

F. Li, T. Zhang, Q. Wang, M. Gonzalez, E. Maresh, and J.A. Coan (2015). Spatial Bayesian Variable Selection and Grouping in High-dimensional Scalar-on-Image Regressions.The Annals of Applied Statistics 9 (2), 687-713.

E.T. Cirulli, B. N. Lasseigne, S. Petrovski, P. C. Sapp, P. A. Dion, C. S. Leblond, J. Couthouis, Y.F. Lu, Q. Wang, B. J. Krueger, Z. Ren, J. Keebler, Y. Han, S. E. Levy, B. E. Boone, J. R. Wimbish, L. L. Waite, A. L. Jones, J. P. Carulli, A. G. Day-Williams, J. F. Staropoli, W. W. Xin, A. Chesi, A. R. Raphael, D. McKenna-Yasek, J. Cady, J.M.B. Vianney de Jong, K. P. Kenna, B. N. Smith, S. Topp, J. Miller, A. Gkazi, FALS Sequencing Consortium, A. Al-Chalabi, L. H. van den Berg, J. Veldink, V. Silani, N. Ticozzi, C. E. Shaw, R. H. Baloh, S. Appel, E. Simpson, C. Lagier-Tourenne, S. M. Pulst, S. Gibson, J. Q. Trojanowski, L. Elman, L. McCluskey, M. Grossman, N. A. Shneider, W. K. Chung, J. M. Ravits, J. D. Glass, K. B. Sims, V. M. Van Deerlin, T. Maniatis, S. D. Hayes, A. Ordureau, S. Swarup, J. Landers, F. Baas, A. S. Allen, R. S. Bedlack, J. W. Harper, A. D. Gitler, G. A. Rouleau, R. Brown, M. B. Harms, G. M. Cooper, T. Harris, R. M. Myers, D. B. Goldstein. (2015) Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways. Science DOI: 10.1126/science.aaa3650.

J. Hu, J.P. Reiter and Q. Wang (2014). Disclosure Risk Evaluation for Fully Synthetic Categorical Data. Privacy in Statistical Databases, Lecture Notes in Computer Science 8744 ed. J. Domingo-Ferrer, Springer, 185-199.

J. P. Reiter, Q. Wang and B. E. Zhang (2014) Bayesian Estimation of Disclosure Risks for Multiply Imputed, Synthetic Data. Journal of Privacy and Confidentiality, 6:1, Article 2.

H. J. Kim, J. P. Reiter, Q. Wang, L. H. Cox, and A. F. Karr (2014). Multiple imputation of missing or faulty values under linear constraints. Journal of Business and Economic Statistics. 32(3), p375-386.

S. Petrovski, Q. Wang, E.L. Heinzen, A.S. Allen, D.B. Goldstein (2013). Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes. PLoS Genet 9(8): e1003709. doi:10.1371/journal.pgen.1003709

L. Lin, C. Chan, S.R. Hadrup, Q. Wang, and M. West (2013). Hierarchical Bayesian mixture modelling for combinatorially encoded flow cytometry studies, Statistical Applications in Genetics and Molecular Biology 12, p309-331

B. Yu, A. Shah, B. Wang, N. Rajaram, Q. Wang, N. Ramanujam, G.M. Palmer, M.W. Dewhirst. Measuring tumor cycling hypoxia and angiogenesis using a side-firing fiber optic probe. Journal of Biophotonics. (2012). DOI 10.1002/jbio.201200187

Q. Wang, M. West. Model-controlled flooding with applications to image reconstruction and segmentation. Journal of Electronic Imaging. 21(2012). pp. 023020

Q. Wang, J. Niemi, C.H Tan, L. You, M. West. Image segmentation and dynamic lineage analysis in single-cell fluorescent microscopy. Cytometry A 77(2010). 101-110.

M. Suchard, Q. Wang, C. Chan, J. Frelinger, A. Cron and M. West. "Understanding GPU programming for statistical computation: Studies in massively parallel massive mixtures." Journal of Computational and Graphical Statistics 19 (2010): 419-438.

M. L. Gatza, J.E. Lucus, W.T. Barry, J.W. Kim, Q. Wang, M.D. Crawford, M.B. Datto, M. Kelley, B. Mathey-Prevot, A. Potti and J.R. Nevins. "A pathway-based classification of human breast cancer." PNAS 107(15) (2010), 6994-6999.

J. Chang, C. Carvalho, S. Mori, A. Bild, Q. Wang, M. West, J. Nevins (2009). Decomposing cellular signaling pathways into functional units: A genomic strategy. Molecular Cell 34.1, 104-114.

Q. Wang, L. You & M. West. CellTracer: Software for automated image segmentation and lineage mapping for single-cell studies. Discussion Paper 08-22, Department of Statistical Science, Duke University (2008).

C. Carvalho, J. Lucas, Q. Wang, J. T. Chang, J.R. Nevins, M. West (2008). High-Dimensional Sparse Factor Modelling: Applications in Gene Expression Genomics. Journal of the American Statistical Association 103 (2008): 1438-1456.

Q. Wang, C. Carvalho, J.E. Lucas and M. West (2007). BFRM: Bayesian factor regression modelling. Bulletin of the International Society for Bayesian Analysis 14 (2007): 4-5.

C. Hans, Q. Wang, A. Dobra and M. West. SSS: High-dimensional Bayesian regression model search. Bulletin of the International Society for Bayesian Analysis 24 (2007): 8-9.

J. Lucas, C. Carvalho, Q. Wang, A. Bild, J.R. Nevins and M. West. Sparse statistical modelling in gene expression genomics. Bayesian Inference for Gene Expression and Proteomics (2006): 155-176.

A.H. Bild, G. Yao, J.T. Chang, Q. Wang, A. Potti, D. Chasse, M. Joshi, D. Harpole, J.M. Lancaster, A. Berchuck, J.A. Olson, J.R. Marks, H.K. Dressman, M.West and J.R. Nevins. "Oncogenic pathway signatures in human cancers as a guide to targeted therapies." Nature 439 (2006): 353-357.

M. DeLong, G. Yao, Q. Wang, A. Dobra, E.P. Black, J.T. Chang, Bild, M. West, J.R. Nevins and H. Dressman (2005). DIG - A system for gene annotation and functional discovery. Bioinformatics, 21, 2957 - 2959.

J. Pittman, E. Huang, Q. Wang, J. Nevins and M. West (2004). Binary analysis of binary prediction tree models for retrospectively sampled outcomes. Biostatistics, 5, 587-601.