Publications
21. Wang W, Wei Z, Tak-Wah Lam, and Wang J, Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions,
Scientific Reports,
2011, 1(55).
20. Lyon GJ, Jiang T, Van Wijk R, Wang W, Bodily P,
Xing J, Tian L, Robison R, Clement M, Yang L, Zhang P, Liu Y, Moore
B, Glessner J, Elia J, Reimherr F, van Solinge W, Yandell M,
Hakonarson H, Wang J, Johnson WE, Wei Z, and Wang K. Exome
Sequencing and Unrelated Findings in the Context of Complex Disease
Research: Ethical and Clinical Implications.
Discovery Medicine,
2011 12(62).
19. Wei Z, Wang W, Hu P, Lyon GJ, and Hakonarson
H, SNVer: a statistical tool for variant calling in analysis of pooled or individual next-generation sequencing data,
Nucleic Acids Research,
2011, doi: 10.1093/nar/gkr599.
Software SNVer
18. Roshan U, Chikkagoudar S, Wei Z, Wang K, and Hakonarson
H, Ranking Causal SNPs and Associated Regions in Genome Wide
Association Studies by the Support Vector Machine and Random Forest,
Nucleic Acids Research,
2011 39(9):e62.
17. Sun W and Wei Z,
Multiple Testing for Pattern Identification, with Applications to
Microarray Time Course Experiments,
Journal of the American Statistical Association,
2011 106(493):73–88,
 .
16. Wang W, Wei Z, and
Sun W, Simultaneous
Set-Wise Testing Under Dependence, with Applications to Genome-Wide
Association Studies,
Statistics and Its Interface,
2010
3(4):501-512.
15. Wei Z, Hidden Markov Models for Controlling False Discovery Rate in Genome-Wide Association Analysis,
Next
generation microarray bioinformatics, Humana Press and Springer, edited by
Wang J., Tan A. and Tian T.
14. Li C, Wei Z, and
Li H, Network-based Empirical Bayes Methods for Linear Models
with Applications to Genomic Data,
Journal of Biopharmaceutical Statistics,
2010 20(2):209-222.
13.
Li H, Wei Z and
Maris J, A Hidden Markov Random Field Model for Genome-wide
Association Studies, Biostatistics, 2010, 11:139-150.
12. Hu P*, Wei Z*, Wang Z, Paterson AD, Beyene J and Scherer SW, Scoring of ChIP-seq experiments by modeling large-scale correlated tests,
CAMDA 2009
(*Equally Contributed)
11. Wei Z,
Wang K, Qu H, Zhang H, Bradfield J, Kim C, Frackleton E, Hou C, Glessner JT, Chiavacci R, Stanley C, Monos D, Grant SFA, Polychronakos C and Hakonarson H, From Association to Disease Risk Prediction: an Optimistic View from Genome-wide Association Studies on Type 1 Diabetes, PLoS Genetics,
2009, 5(10): e1000678
10. Wei Z,
Sun W,
Wang K and Hakonarson H, Multiple Testing in Genome-Wide Association Studies via Hidden Markov Models, Bioinformatics, 2009 25:2802-2808,
Software PLIS.
09. Wei Z, Minturn J, Rappaport E,
Brodeur G and Li
H, Network-based Analysis of Multivariate Gene Expression Data, Statistical Methods for Microarray Data Analysis,
Humana Press and Springer, edited by Yakovle A,
Klebanov L and Gaile G
08. Braunstein
A, Wei Z, Jensen
ST and McAuliffe
J, A Spatially Varying Two-sample Recombinant Coalescent, with
Applications to HIV Escape Response, Advances in Neural Information
Processing Systems 21 (NIPS2008), 2009, 193-200
07. Wei Z, Li
M, Rebeck
T and Li
H, U-Statistics-based Tests for Multiple Genes in Genetic Association
Studies, Annals
of Human Genetics, 2008,
72: 821-833
06. Wei Z and Li
H, A Hidden Spatial-temporal Markov Random Field Model for Network-based
Analysis of Time Course Gene Expression Data, Annals
of Applied Statistics, 2008,
2: 408-429
05. Wei Z and Li
M, Genome-wide Association Analysis of Rheumatoid Arthritis in
a Canadian Population, BMC
Proceedings, 2007,
1(Suppl 1):S19
04. Wei Z and Li
H, A Markov Random Field Model for Network-based Analysis of
Genomic Data, Bioinformatics,
2007 23:1537-1544
03. Wei Z and Li
H, Nonparametric Pathway-Based Regression Models for Analysis
of Genomic Data, Biostatistics,
2007 8: 265-284
02. Wei Z and Jensen
ST, GAME: Detecting Cis-regulatory Elements Using a Genetic Algorithm, Bioinformatics,
2006
22:1577-1584,
Software GAME.
01. Yan Z, Wei Z and Kang L, Exploiting the Marginal Profits
of Constraints with Evolutionary Multi-objective Optimization Techniques, Proceedings of the International Conference on Artificial Intelligence,
IC-AI 2003: 251-256
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