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.
150 related articles for article (PubMed ID: 24529200)
1. Empirical evaluation of consistency and accuracy of methods to detect differentially expressed genes based on microarray data. Yang D; Parrish RS; Brock GN Comput Biol Med; 2014 Mar; 46():1-10. PubMed ID: 24529200 [TBL] [Abstract][Full Text] [Related]
2. Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data. Jeffery IB; Higgins DG; Culhane AC BMC Bioinformatics; 2006 Jul; 7():359. PubMed ID: 16872483 [TBL] [Abstract][Full Text] [Related]
3. Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach. Li D; Le Pape MA; Parikh NI; Chen WX; Dye TD PLoS One; 2013; 8(11):e80099. PubMed ID: 24312198 [TBL] [Abstract][Full Text] [Related]
4. Evaluating reproducibility of differential expression discoveries in microarray studies by considering correlated molecular changes. Zhang M; Zhang L; Zou J; Yao C; Xiao H; Liu Q; Wang J; Wang D; Wang C; Guo Z Bioinformatics; 2009 Jul; 25(13):1662-8. PubMed ID: 19417058 [TBL] [Abstract][Full Text] [Related]
5. Investigating the concordance of Gene Ontology terms reveals the intra- and inter-platform reproducibility of enrichment analysis. Zhang L; Zhang J; Yang G; Wu D; Jiang L; Wen Z; Li M BMC Bioinformatics; 2013 Apr; 14():143. PubMed ID: 23627640 [TBL] [Abstract][Full Text] [Related]
6. An evaluation of statistical methods for DNA methylation microarray data analysis. Li D; Xie Z; Pape ML; Dye T BMC Bioinformatics; 2015 Jul; 16():217. PubMed ID: 26156501 [TBL] [Abstract][Full Text] [Related]
7. Sample size for detecting differentially expressed genes in microarray experiments. Wei C; Li J; Bumgarner RE BMC Genomics; 2004 Nov; 5():87. PubMed ID: 15533245 [TBL] [Abstract][Full Text] [Related]
8. Estimating effect sizes of differentially expressed genes for power and sample-size assessments in microarray experiments. Matsui S; Noma H Biometrics; 2011 Dec; 67(4):1225-35. PubMed ID: 21627629 [TBL] [Abstract][Full Text] [Related]
9. Empirical Bayes models for multiple probe type microarrays at the probe level. Astrand M; Mostad P; Rudemo M BMC Bioinformatics; 2008 Mar; 9():156. PubMed ID: 18366694 [TBL] [Abstract][Full Text] [Related]
10. Comparison of small n statistical tests of differential expression applied to microarrays. Murie C; Woody O; Lee AY; Nadon R BMC Bioinformatics; 2009 Feb; 10():45. PubMed ID: 19192265 [TBL] [Abstract][Full Text] [Related]
11. A semi-parametric statistical model for integrating gene expression profiles across different platforms. Lyu Y; Li Q BMC Bioinformatics; 2016 Jan; 17 Suppl 1(Suppl 1):5. PubMed ID: 26818110 [TBL] [Abstract][Full Text] [Related]
12. Arrow plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on sample subgroups. Silva-Fortes C; Amaral Turkman MA; Sousa L BMC Bioinformatics; 2012 Jun; 13():147. PubMed ID: 22734592 [TBL] [Abstract][Full Text] [Related]
13. Parallel multiplicity and error discovery rate (EDR) in microarray experiments. Xu WW; Carter CJ BMC Bioinformatics; 2010 Sep; 11():465. PubMed ID: 20846437 [TBL] [Abstract][Full Text] [Related]
14. [Comparison of statistical methods for detecting differential expression in microarray data]. Shan WJ; Tong CF; Shi JS Yi Chuan; 2008 Dec; 30(12):1640-6. PubMed ID: 19073583 [TBL] [Abstract][Full Text] [Related]
15. An empirical bayes adjustment to increase the sensitivity of detecting differentially expressed genes in microarray experiments. Datta S; Satten GA; Benos DJ; Xia J; Heslin MJ; Datta S Bioinformatics; 2004 Jan; 20(2):235-42. PubMed ID: 14734315 [TBL] [Abstract][Full Text] [Related]
16. Evaluating methods for ranking differentially expressed genes applied to microArray quality control data. Kadota K; Shimizu K BMC Bioinformatics; 2011 Jun; 12():227. PubMed ID: 21639945 [TBL] [Abstract][Full Text] [Related]
18. Robust gene selection methods using weighting schemes for microarray data analysis. Kang S; Song J BMC Bioinformatics; 2017 Sep; 18(1):389. PubMed ID: 28865426 [TBL] [Abstract][Full Text] [Related]
19. Methods for evaluating gene expression from Affymetrix microarray datasets. Jiang N; Leach LJ; Hu X; Potokina E; Jia T; Druka A; Waugh R; Kearsey MJ; Luo ZW BMC Bioinformatics; 2008 Jun; 9():284. PubMed ID: 18559105 [TBL] [Abstract][Full Text] [Related]
20. 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] [Next] [New Search]