178 related articles for article (PubMed ID: 27254731)
1. Principal components analysis and the reported low intrinsic dimensionality of gene expression microarray data.
Lenz M; Müller FJ; Zenke M; Schuppert A
Sci Rep; 2016 Jun; 6():25696. PubMed ID: 27254731
[TBL] [Abstract][Full Text] [Related]
2. Gene expression data classification using locally linear discriminant embedding.
Li B; Zheng CH; Huang DS; Zhang L; Han K
Comput Biol Med; 2010 Oct; 40(10):802-10. PubMed ID: 20864095
[TBL] [Abstract][Full Text] [Related]
3. Spectral embedding finds meaningful (relevant) structure in image and microarray data.
Higgs BW; Weller J; Solka JL
BMC Bioinformatics; 2006 Feb; 7():74. PubMed ID: 16483359
[TBL] [Abstract][Full Text] [Related]
4. Selecting subsets of newly extracted features from PCA and PLS in microarray data analysis.
Li GZ; Bu HL; Yang MQ; Zeng XQ; Yang JY
BMC Genomics; 2008 Sep; 9 Suppl 2(Suppl 2):S24. PubMed ID: 18831790
[TBL] [Abstract][Full Text] [Related]
5. A weighted principal component analysis and its application to gene expression data.
Pinto da Costa JF; Alonso H; Roque L
IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(1):246-52. PubMed ID: 21071812
[TBL] [Abstract][Full Text] [Related]
6. Nonnegative principal component analysis for cancer molecular pattern discovery.
Han X
IEEE/ACM Trans Comput Biol Bioinform; 2010; 7(3):537-49. PubMed ID: 20671323
[TBL] [Abstract][Full Text] [Related]
7. Mining gene expression data by interpreting principal components.
Roden JC; King BW; Trout D; Mortazavi A; Wold BJ; Hart CE
BMC Bioinformatics; 2006 Apr; 7():194. PubMed ID: 16600052
[TBL] [Abstract][Full Text] [Related]
8. Nonlinear dimensionality reduction of gene expression data for visualization and clustering analysis of cancer tissue samples.
Shi J; Luo Z
Comput Biol Med; 2010 Aug; 40(8):723-32. PubMed ID: 20637456
[TBL] [Abstract][Full Text] [Related]
9. Interpretation of ANOVA models for microarray data using PCA.
de Haan JR; Wehrens R; Bauerschmidt S; Piek E; van Schaik RC; Buydens LM
Bioinformatics; 2007 Jan; 23(2):184-90. PubMed ID: 17105717
[TBL] [Abstract][Full Text] [Related]
10. Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data.
Bartenhagen C; Klein HU; Ruckert C; Jiang X; Dugas M
BMC Bioinformatics; 2010 Nov; 11():567. PubMed ID: 21087509
[TBL] [Abstract][Full Text] [Related]
11. Robust PCA and classification in biosciences.
Hubert M; Engelen S
Bioinformatics; 2004 Jul; 20(11):1728-36. PubMed ID: 14988110
[TBL] [Abstract][Full Text] [Related]
12. A novel approach to the clustering of microarray data via nonparametric density estimation.
De Bin R; Risso D
BMC Bioinformatics; 2011 Feb; 12():49. PubMed ID: 21303507
[TBL] [Abstract][Full Text] [Related]
13. Block principal component analysis with application to gene microarray data classification.
Liu A; Zhang Y; Gehan E; Clarke R
Stat Med; 2002 Nov; 21(22):3465-74. PubMed ID: 12407684
[TBL] [Abstract][Full Text] [Related]
14. Accounting for probe-level noise in principal component analysis of microarray data.
Sanguinetti G; Milo M; Rattray M; Lawrence ND
Bioinformatics; 2005 Oct; 21(19):3748-54. PubMed ID: 16091409
[TBL] [Abstract][Full Text] [Related]
15. pcaMethods--a bioconductor package providing PCA methods for incomplete data.
Stacklies W; Redestig H; Scholz M; Walther D; Selbig J
Bioinformatics; 2007 May; 23(9):1164-7. PubMed ID: 17344241
[TBL] [Abstract][Full Text] [Related]
16. Elucidating the altered transcriptional programs in breast cancer using independent component analysis.
Teschendorff AE; Journée M; Absil PA; Sepulchre R; Caldas C
PLoS Comput Biol; 2007 Aug; 3(8):e161. PubMed ID: 17708679
[TBL] [Abstract][Full Text] [Related]
17. Discovering What Dimensionality Reduction Really Tells Us About RNA-Seq Data.
Simmons S; Peng J; Bienkowska J; Berger B
J Comput Biol; 2015 Aug; 22(8):715-28. PubMed ID: 26098139
[TBL] [Abstract][Full Text] [Related]
18. Visualization and analysis of molecular data.
Scholz M; Selbig J
Methods Mol Biol; 2007; 358():87-104. PubMed ID: 17035682
[TBL] [Abstract][Full Text] [Related]
19. Biologically valid linear factor models of gene expression.
Girolami M; Breitling R
Bioinformatics; 2004 Nov; 20(17):3021-33. PubMed ID: 15201181
[TBL] [Abstract][Full Text] [Related]
20. Identifying differential correlation in gene/pathway combinations.
Braun R; Cope L; Parmigiani G
BMC Bioinformatics; 2008 Nov; 9():488. PubMed ID: 19017408
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
