These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
123 related articles for article (PubMed ID: 22994883)
1. A hierarchical semiparametric model for incorporating intergene information for analysis of genomic data. Qu L; Nettleton D; Dekkers JC Biometrics; 2012 Dec; 68(4):1168-77. PubMed ID: 22994883 [TBL] [Abstract][Full Text] [Related]
2. Estimating the false discovery rate using nonparametric deconvolution. van de Wiel MA; Kim KI Biometrics; 2007 Sep; 63(3):806-15. PubMed ID: 17825012 [TBL] [Abstract][Full Text] [Related]
3. MACAT--microarray chromosome analysis tool. Toedling J; Schmeier S; Heinig M; Georgi B; Roepcke S Bioinformatics; 2005 May; 21(9):2112-3. PubMed ID: 15572464 [TBL] [Abstract][Full Text] [Related]
4. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies. Noma H; Matsui S Stat Med; 2013 May; 32(11):1904-16. PubMed ID: 23281021 [TBL] [Abstract][Full Text] [Related]
5. Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysis. Nettleton D; Recknor J; Reecy JM Bioinformatics; 2008 Jan; 24(2):192-201. PubMed ID: 18042553 [TBL] [Abstract][Full Text] [Related]
6. Detecting differential gene expression with a semiparametric hierarchical mixture method. Newton MA; Noueiry A; Sarkar D; Ahlquist P Biostatistics; 2004 Apr; 5(2):155-76. PubMed ID: 15054023 [TBL] [Abstract][Full Text] [Related]
7. Microarray data analysis: a hierarchical T-test to handle heteroscedasticity. de Menezes RX; Boer JM; van Houwelingen HC Appl Bioinformatics; 2004; 3(4):229-35. PubMed ID: 15702953 [TBL] [Abstract][Full Text] [Related]
8. Incorporating gene networks into statistical tests for genomic data via a spatially correlated mixture model. Wei P; Pan W Bioinformatics; 2008 Feb; 24(3):404-11. PubMed ID: 18083717 [TBL] [Abstract][Full Text] [Related]
9. A three component latent class model for robust semiparametric gene discovery. Alfo' M; Farcomeni A; Tardella L Stat Appl Genet Mol Biol; 2011; 10():Article 7. PubMed ID: 21291417 [TBL] [Abstract][Full Text] [Related]
10. A mixture model with random-effects components for clustering correlated gene-expression profiles. Ng SK; McLachlan GJ; Wang K; Ben-Tovim Jones L; Ng SW Bioinformatics; 2006 Jul; 22(14):1745-52. PubMed ID: 16675467 [TBL] [Abstract][Full Text] [Related]
11. Segmentation and intensity estimation of microarray images using a gamma-t mixture model. Baek J; Son YS; McLachlan GJ Bioinformatics; 2007 Feb; 23(4):458-65. PubMed ID: 17166856 [TBL] [Abstract][Full Text] [Related]
12. A new outlier removal approach for cDNA microarray normalization. Wu Y; Yan L; Liu H; Sun H; Xie H Biotechniques; 2009 Aug; 47(2):691-2, 694-700. PubMed ID: 19737130 [TBL] [Abstract][Full Text] [Related]
13. ARSyN: a method for the identification and removal of systematic noise in multifactorial time course microarray experiments. Nueda MJ; Ferrer A; Conesa A Biostatistics; 2012 Jul; 13(3):553-66. PubMed ID: 22085896 [TBL] [Abstract][Full Text] [Related]
15. A spline function approach for detecting differentially expressed genes in microarray data analysis. He W Bioinformatics; 2004 Nov; 20(17):2954-63. PubMed ID: 15180936 [TBL] [Abstract][Full Text] [Related]
16. A GMM-IG framework for selecting genes as expression panel biomarkers. Wang M; Chen JY Artif Intell Med; 2010; 48(2-3):75-82. PubMed ID: 20004087 [TBL] [Abstract][Full Text] [Related]
17. ChroCoLoc: an application for calculating the probability of co-localization of microarray gene expression. Blake J; Schwager C; Kapushesky M; Brazma A Bioinformatics; 2006 Mar; 22(6):765-7. PubMed ID: 16377611 [TBL] [Abstract][Full Text] [Related]