Publications by Yuehua Cui

Selected peer-referred journal articles (*corresponding author; Trainee)

1.       Gao, B.#, X. Liu#, H.Z. Li and Y.H. Cui*. (2019) Integrative analysis of genetical genomics data incorporating network structures. Biometrics Methodology  [code] (# The first two authors contributed equally to this work)

  1. Liu, X., P-S. Zhong and Y.H. Cui*. (2019) Joint test of parametric and nonparametric effects in partial linear models for gene-environment interaction. Statistica Sinica (in press)
  2. Wu, C., P-S. Zhong and Y.H. Cui*. (2018) Additive varying-coefficient model for nonlinear gene-environment interactions. Statistical Applications in Genetics and Molecular Biology 17: 2.

4.       Wang, H., P-S. Zhong* and Y.H. Cui. (2018) Empirical likelihood ratio tests for coefficients in high dimensional heteroscedastic linear models. Statistica Sinica 28: 2409-2433.

  1. Wang, H.L., P-S. Zhong*, Y.H. Cui and Y. Li. (2018) Unified empirical likelihood ratio tests for functional concurrent linear models and the phase transition from sparse to dense functional data. [Supplemental files] Journal of the Royal Statistical Society B 80(2): 343-364.

6.       Wu, C., Y. Jiang, J. Ren, Y.H. Cui and S. Ma. (2018) Dissecting gene-environment interactions: a penalized robust approach accounting for hierarchical structures. Statistics in Medicine 37(3): 437-456.

  1. Cui, Y.H.* and H. Yang. (2017) Dissecting genomic imprinting and genetic conflict from a game theory prospective: Comment on: “Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition” by Qian Wang et al. Physics of Life Reviews 20: 161-163.

8.       Li, G. and Y.H. Cui*. (2016) Assessing statistical significance in variance components linkage analysis: a theoretical justification. Journal of Statistical Planning and Inference 178: 70-83 [PDF]

9.       Liu, X., Y.H. Cui* and R. Li. (2016) Partial linear varying multi-index coefficient model for integrative gene-environment interactions. [Supplemental file] Statistica Sinica 26: 1037-1060

10.  Li, G., Y.H. Cui and H. Zhao. (2015) An empirical Bayes risk prediction model for multiple traits using sequencing data. Statistical Applications in Genetics and Molecular Biology 14(6): 551-73.

  1. Wu, C., X. Shi, Y.H. Cui and S.G. Ma. (2015) A penalized robust semi-parametric approach for gene-environment interactions. Statistics in Medicine 34(30):4016-30.
  2. Gao, B. and Y.H. Cui*. (2015) Learning directed acyclic graphical structures with genetical genomics data. Bioinformatics 31:3953-3960.
  3. Wu, C., Y.H. Cui and S.G. Ma. (2014) Integrative analysis of gene-environment interactions under a multi-response partially linear varying coefficient model. Statistics in Medicine 33: 4988-4998.
  4. Dai, H.Y., T. Srivastava, and Y.H. Cui. (2014) A modified generalized fisher method for combining probabilities from dependent tests. Frontiers in Genetics 5:23.
  5. Kim, D-Y., Y.H. Cui and O. Zhao. (2013) Asymptotic test of mixture model and its applications to QTL interval mapping. Journal of Statistical Planning and Inference 143: 1320-1329.

16.  Geu-Flores, F., N.H. Sherden, V. Courdavault, V. Burlat, W.S. Glenn, C. Wu, E. Nims, Y.H. Cui, and S.E. O’Connor. (2012) An alternative route to cyclic terpenes by reductive cyclization in iridoid biosynthesis. Nature 492: 138–142 doi:10.1038/nature11692

  1. Li, S.Y. and Y.H. Cui*. (2012) Gene-centric gene-gene interaction: a model-based kernel machine method. Annals of Applied Statistics [ PDF] 6(3): 1134-1161.
  2. Li, S.Y., B. Williams and Y.H. Cui*. (2011) A combined p-value approach to infer pathway regulations in eQTL mapping. Statistics and Its Interface 4(3): 389-402 [PDF] (invited)
  3. Ma, S.J., L.J. Yang, R. Romero, and Y.H. Cui*. (2011) Varying coefficient model for gene-environment interaction: a non-linear look. Bioinformatics 27(15): 2119-2126.
  4. Li, G.X. and Y.H. Cui*. (2010) A general statistical framework for dissecting parent-of-origin effects underlying triploid endosperm traits in flowering plants. Annals of Applied Statistics 4(3): 1214-1233. [PDF]|[Link to the Journal].
  5. Li, S.Y., Q. Lu, W. Fu, R. Romero and Y.H. Cui*. (2009) A regularized regression approach for dissecting genetic conflicts that increase disease risk in pregnancy. Statistical Applications in Genetics and Molecular Biology Vol. 8 : Iss. 1, Article 45. [PubMed]
  6. Cui, Y.H.* and W.Z. Yang. (2009) Zero inflated generalized poisson regression mixture model for mapping quantitative trait loci underlying count trait with many zeros. Journal of Theoretical Biology 256: 276-285 [PubMed].
  7. Cui, Y.H.*, G.L. Kang, K.L. Sun, R. Romero, M. Qian, and W.J. Fu. (2008) Gene-centric genomewide association study via entropy. Genetics 179: 637-650 [Link] | [ PubMed]. (This work was highlighted in Nature Reviews Genetics)
  8. Cui, Y.H.*, J.M. Cheverud and R.L. Wu. (2007) A statistical model for dissecting genomic imprinting through genetic mapping. Genetica 130: 227-239 [PubMed].
  9. Cui, Y.H.* (2007) A statistical framework for genome-wide scanning and testing imprinted quantitative trait loci. Journal of Theoretical Biology 244: 115-126 [PubMed].
  10. Cui, Y.H.*, D.-Y. Kim, and J. Zhu. (2006) On the generalized Poisson regression mixture model for mapping quantitative trait loci with count data. Genetics 174(4): 2159-2172. [PubMed].
  11. Cui, Y.H., J. Zhu, and R.L. Wu. (2006) Functional mapping for genetic control of programmed cell death. Physiological Genomics 25: 458-469 [PubMed].
  12. Cui, Y.H. and R.L. Wu. (2005) Mapping genome-genome epistasis: A high-dimensional model. Bioinformatics 21(10): 2447-2455 [PubMed].
  13. Cui, Y. H., G. Casella and R.L. Wu. (2004) Mapping quantitative trait loci interactions from the maternal and offspring genomes. Genetics, 167: 1017-1026 [PubMed].

Research Highlight

Last Modified in 2018