BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

171 related articles for article (PubMed ID: 17369631)

  • 1. Pem: a general statistical approach for identifying differentially expressed genes in time-course cDNA microarray experiment without replicate.
    Han X; Sung WK; Feng L
    Comput Syst Bioinformatics Conf; 2006; ():123-32. PubMed ID: 17369631
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Identifying differentially expressed genes in time-course microarray experiment without replicate.
    Han X; Sung WK; Feng L
    J Bioinform Comput Biol; 2007 Apr; 5(2a):281-96. PubMed ID: 17589962
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments.
    Liu H; Tarima S; Borders AS; Getchell TV; Getchell ML; Stromberg AJ
    BMC Bioinformatics; 2005 Apr; 6():106. PubMed ID: 15850479
    [TBL] [Abstract][Full Text] [Related]  

  • 4. In silico microdissection of microarray data from heterogeneous cell populations.
    Lähdesmäki H; Shmulevich L; Dunmire V; Yli-Harja O; Zhang W
    BMC Bioinformatics; 2005 Mar; 6():54. PubMed ID: 15766384
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data.
    Xie Y; Pan W; Khodursky AB
    Bioinformatics; 2005 Dec; 21(23):4280-8. PubMed ID: 16188930
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Quantitative inference of dynamic regulatory pathways via microarray data.
    Chang WC; Li CW; Chen BS
    BMC Bioinformatics; 2005 Mar; 6():44. PubMed ID: 15748298
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The influence of missing value imputation on detection of differentially expressed genes from microarray data.
    Scheel I; Aldrin M; Glad IK; Sørum R; Lyng H; Frigessi A
    Bioinformatics; 2005 Dec; 21(23):4272-9. PubMed ID: 16216830
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Unbiased pattern detection in microarray data series.
    Ahnert SE; Willbrand K; Brown FC; Fink TM
    Bioinformatics; 2006 Jun; 22(12):1471-6. PubMed ID: 16766565
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Construction of null statistics in permutation-based multiple testing for multi-factorial microarray experiments.
    Gao X
    Bioinformatics; 2006 Jun; 22(12):1486-94. PubMed ID: 16574697
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An adaptive method for cDNA microarray normalization.
    Zhao Y; Li MC; Simon R
    BMC Bioinformatics; 2005 Feb; 6():28. PubMed ID: 15707486
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Normal uniform mixture differential gene expression detection for cDNA microarrays.
    Dean N; Raftery AE
    BMC Bioinformatics; 2005 Jul; 6():173. PubMed ID: 16011807
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A general framework for analyzing data from two short time-series microarray experiments.
    Shah M; Corbeil J
    IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(1):14-26. PubMed ID: 21071793
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Ranking analysis for identifying differentially expressed genes.
    Qi Y; Sun H; Sun Q; Pan L
    Genomics; 2011 May; 97(5):326-9. PubMed ID: 21402142
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A robust two-way semi-linear model for normalization of cDNA microarray data.
    Wang D; Huang J; Xie H; Manzella L; Soares MB
    BMC Bioinformatics; 2005 Jan; 6():14. PubMed ID: 15663789
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data.
    Shedden K; Chen W; Kuick R; Ghosh D; Macdonald J; Cho KR; Giordano TJ; Gruber SB; Fearon ER; Taylor JM; Hanash S
    BMC Bioinformatics; 2005 Feb; 6():26. PubMed ID: 15705192
    [TBL] [Abstract][Full Text] [Related]  

  • 16. maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments.
    Conesa A; Nueda MJ; Ferrer A; Talón M
    Bioinformatics; 2006 May; 22(9):1096-102. PubMed ID: 16481333
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Exploratory differential gene expression analysis in microarray experiments with no or limited replication.
    Loguinov AV; Mian IS; Vulpe CD
    Genome Biol; 2004; 5(3):R18. PubMed ID: 15003121
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Two-part permutation tests for DNA methylation and microarray data.
    Neuhäuser M; Boes T; Jöckel KH
    BMC Bioinformatics; 2005 Feb; 6():35. PubMed ID: 15725357
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein.
    Raghava GP; Han JH
    BMC Bioinformatics; 2005 Mar; 6():59. PubMed ID: 15773999
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Using weighted permutation scores to detect differential gene expression with microarray data.
    Guo X; Pan W
    J Bioinform Comput Biol; 2005 Aug; 3(4):989-1006. PubMed ID: 16078371
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.