329 related articles for article (PubMed ID: 16872483)
1. 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]
2. 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]
3. A comparative study of different machine learning methods on microarray gene expression data.
Pirooznia M; Yang JY; Yang MQ; Deng Y
BMC Genomics; 2008; 9 Suppl 1(Suppl 1):S13. PubMed ID: 18366602
[TBL] [Abstract][Full Text] [Related]
4. Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets.
Gormley M; Dampier W; Ertel A; Karacali B; Tozeren A
BMC Bioinformatics; 2007 Oct; 8():415. PubMed ID: 17963508
[TBL] [Abstract][Full Text] [Related]
5. A unified framework for finding differentially expressed genes from microarray experiments.
Shaik JS; Yeasin M
BMC Bioinformatics; 2007 Sep; 8():347. PubMed ID: 17877806
[TBL] [Abstract][Full Text] [Related]
6. Feature selection and classification for microarray data analysis: evolutionary methods for identifying predictive genes.
Jirapech-Umpai T; Aitken S
BMC Bioinformatics; 2005 Jun; 6():148. PubMed ID: 15958165
[TBL] [Abstract][Full Text] [Related]
7. Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.
Nguyen T; Khosravi A; Creighton D; Nahavandi S
PLoS One; 2015; 10(3):e0120364. PubMed ID: 25823003
[TBL] [Abstract][Full Text] [Related]
8. Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data.
Ooi CH; Chetty M; Teng SW
BMC Bioinformatics; 2006 Jun; 7():320. PubMed ID: 16796748
[TBL] [Abstract][Full Text] [Related]
9. Feature selection and nearest centroid classification for protein mass spectrometry.
Levner I
BMC Bioinformatics; 2005 Mar; 6():68. PubMed ID: 15788095
[TBL] [Abstract][Full Text] [Related]
10. The feature selection bias problem in relation to high-dimensional gene data.
Krawczuk J; Łukaszuk T
Artif Intell Med; 2016 Jan; 66():63-71. PubMed ID: 26674595
[TBL] [Abstract][Full Text] [Related]
11. Outcome prediction based on microarray analysis: a critical perspective on methods.
Zervakis M; Blazadonakis ME; Tsiliki G; Danilatou V; Tsiknakis M; Kafetzopoulos D
BMC Bioinformatics; 2009 Feb; 10():53. PubMed ID: 19200394
[TBL] [Abstract][Full Text] [Related]
12. Comparison of feature selection methods for cross-laboratory microarray analysis.
Liu HC; Peng PC; Hsieh TC; Yeh TC; Lin CJ; Chen CY; Hou JY; Shih LY; Liang DC
IEEE/ACM Trans Comput Biol Bioinform; 2013; 10(3):593-604. PubMed ID: 24091394
[TBL] [Abstract][Full Text] [Related]
13. Stratification bias in low signal microarray studies.
Parker BJ; Günter S; Bedo J
BMC Bioinformatics; 2007 Sep; 8():326. PubMed ID: 17764577
[TBL] [Abstract][Full Text] [Related]
14. Mining published lists of cancer related microarray experiments: identification of a gene expression signature having a critical role in cell-cycle control.
Finocchiaro G; Mancuso F; Muller H
BMC Bioinformatics; 2005 Dec; 6 Suppl 4(Suppl 4):S14. PubMed ID: 16351740
[TBL] [Abstract][Full Text] [Related]
15. GEOlimma: differential expression analysis and feature selection using pre-existing microarray data.
Lu L; Townsend KA; Daigle BJ
BMC Bioinformatics; 2021 Feb; 22(1):44. PubMed ID: 33535967
[TBL] [Abstract][Full Text] [Related]
16. Rank-based methods as a non-parametric alternative of the T-statistic for the analysis of biological microarray data.
Breitling R; Herzyk P
J Bioinform Comput Biol; 2005 Oct; 3(5):1171-89. PubMed ID: 16278953
[TBL] [Abstract][Full Text] [Related]
17. Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery.
Grate LR
BMC Bioinformatics; 2005 Apr; 6():97. PubMed ID: 15826317
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. Laplacian linear discriminant analysis approach to unsupervised feature selection.
Niijima S; Okuno Y
IEEE/ACM Trans Comput Biol Bioinform; 2009; 6(4):605-14. PubMed ID: 19875859
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]