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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

87 related articles for article (PubMed ID: 12930160)

  • 1. Assessing the variability in GeneChip data.
    Huang S; Qian HR; Geringer C; Love C; Gelbert L; Bemis K
    Am J Pharmacogenomics; 2003; 3(4):279-90. PubMed ID: 12930160
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data.
    Jones L; Goldstein DR; Hughes G; Strand AD; Collin F; Dunnett SB; Kooperberg C; Aragaki A; Olson JM; Augood SJ; Faull RL; Luthi-Carter R; Moskvina V; Hodges AK
    BMC Bioinformatics; 2006 Apr; 7():211. PubMed ID: 16623940
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Exploration, normalization, and summaries of high density oligonucleotide array probe level data.
    Irizarry RA; Hobbs B; Collin F; Beazer-Barclay YD; Antonellis KJ; Scherf U; Speed TP
    Biostatistics; 2003 Apr; 4(2):249-64. PubMed ID: 12925520
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Sources of variation in Affymetrix microarray experiments.
    Zakharkin SO; Kim K; Mehta T; Chen L; Barnes S; Scheirer KE; Parrish RS; Allison DB; Page GP
    BMC Bioinformatics; 2005 Aug; 6():214. PubMed ID: 16124883
    [TBL] [Abstract][Full Text] [Related]  

  • 5. At what scale should microarray data be analyzed?
    Huang S; Yeo AA; Gelbert L; Lin X; Nisenbaum L; Bemis KG
    Am J Pharmacogenomics; 2004; 4(2):129-39. PubMed ID: 15059035
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Characterization of variability in large-scale gene expression data: implications for study design.
    Novak JP; Sladek R; Hudson TJ
    Genomics; 2002 Jan; 79(1):104-13. PubMed ID: 11827463
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Sources of variability and effect of experimental approach on expression profiling data interpretation.
    Bakay M; Chen YW; Borup R; Zhao P; Nagaraju K; Hoffman EP
    BMC Bioinformatics; 2002; 3():4. PubMed ID: 11936955
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A new method for class prediction based on signed-rank algorithms applied to Affymetrix microarray experiments.
    Rème T; Hose D; De Vos J; Vassal A; Poulain PO; Pantesco V; Goldschmidt H; Klein B
    BMC Bioinformatics; 2008 Jan; 9():16. PubMed ID: 18190711
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A comparison of cDNA, oligonucleotide, and Affymetrix GeneChip gene expression microarray platforms.
    Woo Y; Affourtit J; Daigle S; Viale A; Johnson K; Naggert J; Churchill G
    J Biomol Tech; 2004 Dec; 15(4):276-84. PubMed ID: 15585824
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A graphical approach for quality control of oligonucleotide array data.
    Chen DT
    J Biopharm Stat; 2004 Aug; 14(3):591-606. PubMed ID: 15468754
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis.
    Holloway AJ; Oshlack A; Diyagama DS; Bowtell DD; Smyth GK
    BMC Bioinformatics; 2006 Nov; 7():511. PubMed ID: 17118209
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements.
    Carter SL; Eklund AC; Mecham BH; Kohane IS; Szallasi Z
    BMC Bioinformatics; 2005 Apr; 6():107. PubMed ID: 15850491
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Effect of normalization on significance testing for oligonucleotide microarrays.
    Parrish RS; Spencer HJ
    J Biopharm Stat; 2004 Aug; 14(3):575-89. PubMed ID: 15468753
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Summarizing probe intensities of affymetrix GeneChip 3' expression arrays taking into account day-to-day variability.
    Magni P; Simeone A; Healy S; Isacchi A; Bosotti R
    IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(5):1425-30. PubMed ID: 21778528
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparing three methods for variance estimation with duplicated high density oligonucleotide arrays.
    Huang X; Pan W
    Funct Integr Genomics; 2002 Aug; 2(3):126-33. PubMed ID: 12185460
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Gibbs sampler for the identification of gene expression and network connectivity consistency.
    Brynildsen MP; Tran LM; Liao JC
    Bioinformatics; 2006 Dec; 22(24):3040-6. PubMed ID: 17060361
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Quality Control Usage in High-Density Microarrays Reveals Differential Gene Expression Profiles in Ovarian Cancer.
    Villegas-Ruiz V; Moreno J; Jacome-Lopez K; Zentella-Dehesa A; Juarez-Mendez S
    Asian Pac J Cancer Prev; 2016; 17(5):2519-25. PubMed ID: 27268623
    [TBL] [Abstract][Full Text] [Related]  

  • 18. AnovArray: a set of SAS macros for the analysis of variance of gene expression data.
    Hennequet-Antier C; Chiapello H; Piot K; Degrelle S; Hue I; Renard JP; Rodolphe F; Robin S
    BMC Bioinformatics; 2005 Jun; 6():150. PubMed ID: 15960854
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Evaluating concentration estimation errors in ELISA microarray experiments.
    Daly DS; White AM; Varnum SM; Anderson KK; Zangar RC
    BMC Bioinformatics; 2005 Jan; 6():17. PubMed ID: 15673468
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Statistics for ChIP-chip and DNase hypersensitivity experiments on NimbleGen arrays.
    Scacheri PC; Crawford GE; Davis S
    Methods Enzymol; 2006; 411():270-82. PubMed ID: 16939795
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 5.