title: A semiparametric Bayesian approach for estimating the gene expression distribution.
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. fzou@bios.unc.edu
authors.forename: Fei
authors.initials: F
authors.lastname: Zou
authors.forename: Hanwen
authors.initials: H
authors.lastname: Huang
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Ibrahim
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004195:Disease Models, Animal; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D005786:Gene Expression Regulation; D020022:Genetic Predisposition to Disease; D008390:Markov Chains; D051379:Mice; D008807:Mice, Inbred BALB C; D008810:Mice, Inbred C57BL; D015233:Models, Statistical; D009010:Monte Carlo Method; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D011658:Pulmonary Fibrosis / Q000235:genetics; D015203:Reproducibility of Results; D018401:Sample Size; D013045:Species Specificity