117 related articles for article (PubMed ID: 19119428)
1. Comparison of statistical data models for identifying differentially expressed genes using a generalized likelihood ratio test.
Seng KY; Glenny RW; Madtes DK; Spilker ME; Vicini P; Gharib SA
Gene Regul Syst Bio; 2008; 2():125-139. PubMed ID: 19119428
[TBL] [Abstract][Full Text] [Related]
2. A generalized likelihood ratio test to identify differentially expressed genes from microarray data.
Wang S; Ethier S
Bioinformatics; 2004 Jan; 20(1):100-4. PubMed ID: 14693815
[TBL] [Abstract][Full Text] [Related]
3. Distributional fold change test - a statistical approach for detecting differential expression in microarray experiments.
Farztdinov V; McDyer F
Algorithms Mol Biol; 2012 Nov; 7(1):29. PubMed ID: 23122055
[TBL] [Abstract][Full Text] [Related]
4. Evaluation of a statistical equivalence test applied to microarray data.
Qiu J; Cui X
J Biopharm Stat; 2010 Mar; 20(2):240-66. PubMed ID: 20309757
[TBL] [Abstract][Full Text] [Related]
5. Using a Generalized Logistic Regression Method to Detect Differential Item Functioning With Multiple Groups in Cognitive Diagnostic Tests.
Sun X; Wang S; Guo L; Xin T; Song N
Appl Psychol Meas; 2023 Jun; 47(4):328-346. PubMed ID: 37283590
[TBL] [Abstract][Full Text] [Related]
6. Likelihood-based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study.
den Dekker AJ; Poot DH; Bos R; Sijbers J
IEEE Trans Med Imaging; 2009 Feb; 28(2):287-96. PubMed ID: 19188115
[TBL] [Abstract][Full Text] [Related]
7. Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide arrays.
Barrera L; Benner C; Tao YC; Winzeler E; Zhou Y
BMC Bioinformatics; 2004 Apr; 5():42. PubMed ID: 15099405
[TBL] [Abstract][Full Text] [Related]
8. Selection of differentially expressed genes in microarray data analysis.
Chen JJ; Wang SJ; Tsai CA; Lin CJ
Pharmacogenomics J; 2007 Jun; 7(3):212-20. PubMed ID: 16940966
[TBL] [Abstract][Full Text] [Related]
9. Nonparametric methods for identifying differentially expressed genes in microarray data.
Troyanskaya OG; Garber ME; Brown PO; Botstein D; Altman RB
Bioinformatics; 2002 Nov; 18(11):1454-61. PubMed ID: 12424116
[TBL] [Abstract][Full Text] [Related]
10. Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data.
Ideker T; Thorsson V; Siegel AF; Hood LE
J Comput Biol; 2000; 7(6):805-17. PubMed ID: 11382363
[TBL] [Abstract][Full Text] [Related]
11. Statistical inferences for single-index models with measurement errors.
Huang Z; Lou W
J Appl Stat; 2021; 48(6):1033-1052. PubMed ID: 35707736
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. A nonparametric likelihood ratio test to identify differentially expressed genes from microarray data.
Bokka S; Mathur SK
Appl Bioinformatics; 2006; 5(4):267-76. PubMed ID: 17140273
[TBL] [Abstract][Full Text] [Related]
15. Bayesian hierarchical error model for analysis of gene expression data.
Cho H; Lee JK
Bioinformatics; 2004 Sep; 20(13):2016-25. PubMed ID: 15044230
[TBL] [Abstract][Full Text] [Related]
16. Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments.
Zhao H; Chan KL; Cheng LM; Yan H
BMC Bioinformatics; 2008; 9 Suppl 1(Suppl 1):S9. PubMed ID: 18315862
[TBL] [Abstract][Full Text] [Related]
17. A Survey and Comparative Study of Statistical Tests for Identifying Differential Expression from Microarray Data.
Bandyopadhyay S; Mallik S; Mukhopadhyay A
IEEE/ACM Trans Comput Biol Bioinform; 2014; 11(1):95-115. PubMed ID: 26355511
[TBL] [Abstract][Full Text] [Related]
18. Comparison of GLR and invariant detectors under structured clutter covariance.
Kim HS; Hero AO
IEEE Trans Image Process; 2001; 10(10):1509-20. PubMed ID: 18255494
[TBL] [Abstract][Full Text] [Related]
19. A Leveraged Signal-to-Noise Ratio (LSTNR) Method to Extract Differentially Expressed Genes and Multivariate Patterns of Expression From Noisy and Low-Replication RNAseq Data.
Lozoya OA; Santos JH; Woychik RP
Front Genet; 2018; 9():176. PubMed ID: 29868123
[TBL] [Abstract][Full Text] [Related]
20. A likelihood-based method for testing for nonstochastic variation of diversification rates in phylogenies.
McConway KJ; Sims HJ
Evolution; 2004 Jan; 58(1):12-23. PubMed ID: 15058715
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
