- AlbertJ.H. and Chib.S. (1993) Bayesian Analysis of binary and polychotomous response data, Journal of the American Statistical Association., 88: 669–679.
- BaeK and MallickB. (2004) Gene selection using a two-level hierarchical Bayesian model, Bioinformatics., 20: 3423–3430.
- BezdekJ.C. (1981) Pattern Recognition with Fuzzy objective function algorithms. Plenum Press, New York.
- BrownP.J., VannucciM. and FearnT. (1998) Multivariate Bayesian variable selection and prediction. Journal of the Royal Statistical Society: Series B (Statistical Methodology)., 60: 627–641.
- BrownP.O. and BotsteinD. (1999) Exploring the new world of the genome with DNA microarrays. Nature Genetics., 21 (Suppl.): 33–37.
- ChenY., DoughertyE.R. and BittnerM.L. (1997) Ratio-based decisions and the quantitative analysis of cDNA microarray images. Journal of Biomedical Optics., 2: 364–374.
- ChoJ.H., LeeD.K., ParkJ.H., KimK.W. and LeeI.B. (2002) Optimal approaches for classification of acute leukemia subtypes based on gene expression data, Biotechnology Progress., 18,4:847–854.
- De RisiJ.L., IyerV.R., and BrownP.O. (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science., 278:680–686.
- DembeleD and KastnerP (2003) Fuzzy C-means method for clustering microarray data, Bioinformatics., Vol. 19, no. 8:973–980.
- DudoitS., YangY.H., CallowM.J. and SpeedT. (2000) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Technical Report, Department of Statistics, University of California, Berkeley, USA.
- EisenM.B., SpellmanP.T., BrownP.O. and BotsteinD. (1998) Cluster analysis and display of genome-wide expression patterns. Proceedings of National Academy of Sciences, USA., 95: 14863–14868.
- GeorgeE. I., and McCulloch.R. E. (1997) Approaches for Bayesian variable selection. Statistica Sinica., 7: 339–374.
- GilksW., RichardsonS. and SpiegelhalterD. (1996) Markov Chain Monte Carlo in practice, Chapman and Hall, London.
- GolubT. R., SlonimD. K., TamayoP., HuardC., GaasenbeekM., MesirovJ. P., CollerH., LohM. L., DowningJ. R., CaligiuriM. A., BloomfieldC. D. & LanderE. S. (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science., 286: 531–537.
- HastieT., TibshiraniR., EisenM.B., AlizadehA., LevyR., StaudtL., ChanW.C., BotsteinD. and BrownP. (2000) Gene shaving as a method for identifying distinct sets of genes with similar expression patterns. Genome Biology., 1: Research0003.1-0003.21.
- KuoL. and MallickB. (1998). Variable Selection for Regression Models, Sankhya B, 60: 65–81.
- LanderE.S. (1999) Array of hope. Nature Genetics., 21(suppl.): 3–4.
- LeeK.E., ShaN., DoughertyE.R., VannucciM., and MallickB.K (2003) Gene selection : a Bayesian variable selection approach. Bioinformatics., 19(1):90–97.
- LipshutzR.J., FodorS.P., GingerasT.R. and LockhartD.J. (1999) High density synthetic oligonucleotide arrays. Nature Genetics., 21(Suppl.): 20–24.
- NewtonM.A., KendziorskiC.M., RichmondC.S., BlattnerF.R., TsuiK.W., (2001) On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarray data. Journal of Computational Biology 8: 37–52.
- RobertC. (1995) Simulation of truncated normal variables. Statistics and computing., 5:121–125.
- SpellmanP.T., SherlockG., ZhangM.Q., IyerV.R., AndersK., EisenM.B., BrownP.O., BotsteinD. and FutcherB. (1998) Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Molecular Biology of the Cell., 9: 3273–3297.
- TadesseM., ShaN. and VannucciM. (2005) Bayesian variable selection in clustering high-dimensional data. Journal of the American Statistical Association., 100: 602–617.
- TamayoP., SlonimD., MesirovJ., ZhuiQ., KitareewaniS., DmitrovskyE., LanderE.S. and GolubT.R. (1999) Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proceedings of National Academy of Sciences, USA,96: 2907–2912.
- TibshiraniR., HastieT., EisenM., RossD., BotsteinD. and BrownP. (1999) Clustering methods for the analysis of DNA microarray data. Technical Report, Department of Statistics, Stanford University.
- WestM., NevinJ.R., MarksJ.R., SpangR. and ZuzanH. (2000) Bayesian regression analysis in the Large p, small n paradigm with application in DNA microarray studies. Technical Report, Duke University.
- Choose new content alerts to be informed about new research of interest to you
- Easy remote access to your institution's subscriptions on any device, from any location
- Save your searches and schedule alerts to send you new results
- Export your search results into a .csv file to support your research