136 related articles for article (PubMed ID: 16981994)
1. Semi-supervised discovery of differential genes.
Oba S; Ishii S
BMC Bioinformatics; 2006 Sep; 7():414. PubMed ID: 16981994
[TBL] [Abstract][Full Text] [Related]
2. Detecting differential expression in microarray data: comparison of optimal procedures.
Perelman E; Ploner A; Calza S; Pawitan Y
BMC Bioinformatics; 2007 Jan; 8():28. PubMed ID: 17257426
[TBL] [Abstract][Full Text] [Related]
3. Accuracy of latent-variable estimation in Bayesian semi-supervised learning.
Yamazaki K
Neural Netw; 2015 Sep; 69():1-10. PubMed ID: 26005790
[TBL] [Abstract][Full Text] [Related]
4. A computationally efficient modular optimal discovery procedure.
Woo S; Leek JT; Storey JD
Bioinformatics; 2011 Feb; 27(4):509-15. PubMed ID: 21186247
[TBL] [Abstract][Full Text] [Related]
5. Bayesian optimal discovery procedure for simultaneous significance testing.
Cao J; Xie XJ; Zhang S; Whitehurst A; White MA
BMC Bioinformatics; 2009 Jan; 10():5. PubMed ID: 19126217
[TBL] [Abstract][Full Text] [Related]
6. Semi-supervised Nonnegative Matrix Factorization for gene expression deconvolution: a case study.
Gaujoux R; Seoighe C
Infect Genet Evol; 2012 Jul; 12(5):913-21. PubMed ID: 21930246
[TBL] [Abstract][Full Text] [Related]
7. Semi-supervised analysis of gene expression profiles for lineage-specific development in the Caenorhabditis elegans embryo.
Qi Y; Missiuro PE; Kapoor A; Hunter CP; Jaakkola TS; Gifford DK; Ge H
Bioinformatics; 2006 Jul; 22(14):e417-23. PubMed ID: 16873502
[TBL] [Abstract][Full Text] [Related]
8. Simultaneous gene clustering and subset selection for sample classification via MDL.
Jörnsten R; Yu B
Bioinformatics; 2003 Jun; 19(9):1100-9. PubMed ID: 12801870
[TBL] [Abstract][Full Text] [Related]
9. Unsupervised fuzzy pattern discovery in gene expression data.
Wu GP; Chan KC; Wong AK
BMC Bioinformatics; 2011; 12 Suppl 5(Suppl 5):S5. PubMed ID: 21989090
[TBL] [Abstract][Full Text] [Related]
10. Reliable classification of two-class cancer data using evolutionary algorithms.
Deb K; Raji Reddy A
Biosystems; 2003 Nov; 72(1-2):111-29. PubMed ID: 14642662
[TBL] [Abstract][Full Text] [Related]
11. An empirical Bayes optimal discovery procedure based on semiparametric hierarchical mixture models.
Noma H; Matsui S
Comput Math Methods Med; 2013; 2013():568480. PubMed ID: 23690877
[TBL] [Abstract][Full Text] [Related]
12. The latent process decomposition of cDNA microarray data sets.
Rogers S; Girolami M; Campbell C; Breitling R
IEEE/ACM Trans Comput Biol Bioinform; 2005; 2(2):143-56. PubMed ID: 17044179
[TBL] [Abstract][Full Text] [Related]
13. Unsupervised clustering in mRNA expression profiles.
Tasoulis DK; Plagianakos VP; Vrahatis MN
Comput Biol Med; 2006 Oct; 36(10):1126-42. PubMed ID: 16246320
[TBL] [Abstract][Full Text] [Related]
14. An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.
Hsu AL; Tang SL; Halgamuge SK
Bioinformatics; 2003 Nov; 19(16):2131-40. PubMed ID: 14594719
[TBL] [Abstract][Full Text] [Related]
15. Unsupervised feature selection via two-way ordering in gene expression analysis.
Ding CH
Bioinformatics; 2003 Jul; 19(10):1259-66. PubMed ID: 12835270
[TBL] [Abstract][Full Text] [Related]
16. A mixture model for estimating the local false discovery rate in DNA microarray analysis.
Liao JG; Lin Y; Selvanayagam ZE; Shih WJ
Bioinformatics; 2004 Nov; 20(16):2694-701. PubMed ID: 15145810
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Interactively optimizing signal-to-noise ratios in expression profiling: project-specific algorithm selection and detection p-value weighting in Affymetrix microarrays.
Seo J; Bakay M; Chen YW; Hilmer S; Shneiderman B; Hoffman EP
Bioinformatics; 2004 Nov; 20(16):2534-44. PubMed ID: 15117752
[TBL] [Abstract][Full Text] [Related]
19. A mixture model approach in gene-gene and gene-environmental interactions for binary phenotypes.
Li L; Yu M; Jason RD; Shen C; Azzouz F; McLeod HL; Borges-Gonzales S; Nguyen A; Skaar T; Desta Z; Sweeney CJ; Flockhart DA
J Biopharm Stat; 2008; 18(6):1150-77. PubMed ID: 18991114
[TBL] [Abstract][Full Text] [Related]
20. Biologically supervised hierarchical clustering algorithms for gene expression data.
Boratyn GM; Datta S; Datta S
Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():5515-8. PubMed ID: 17947147
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]