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 *

285 related articles for article (PubMed ID: 19689953)

  • 1. Statistical methods for gene set co-expression analysis.
    Choi Y; Kendziorski C
    Bioinformatics; 2009 Nov; 25(21):2780-6. PubMed ID: 19689953
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Differential regulation enrichment analysis via the integration of transcriptional regulatory network and gene expression data.
    Ma S; Jiang T; Jiang R
    Bioinformatics; 2015 Feb; 31(4):563-71. PubMed ID: 25322838
    [TBL] [Abstract][Full Text] [Related]  

  • 3. EBSeq-HMM: a Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments.
    Leng N; Li Y; McIntosh BE; Nguyen BK; Duffin B; Tian S; Thomson JA; Dewey CN; Stewart R; Kendziorski C
    Bioinformatics; 2015 Aug; 31(16):2614-22. PubMed ID: 25847007
    [TBL] [Abstract][Full Text] [Related]  

  • 4. EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments.
    Leng N; Dawson JA; Thomson JA; Ruotti V; Rissman AI; Smits BM; Haag JD; Gould MN; Stewart RM; Kendziorski C
    Bioinformatics; 2013 Apr; 29(8):1035-43. PubMed ID: 23428641
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA.
    Nueda MJ; Conesa A; Westerhuis JA; Hoefsloot HC; Smilde AK; Talón M; Ferrer A
    Bioinformatics; 2007 Jul; 23(14):1792-800. PubMed ID: 17519250
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A new gene selection procedure based on the covariance distance.
    Hu R; Qiu X; Glazko G
    Bioinformatics; 2010 Feb; 26(3):348-54. PubMed ID: 19996162
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Matching methods for observational microarray studies.
    Heller R; Manduchi E; Small DS
    Bioinformatics; 2009 Apr; 25(7):904-9. PubMed ID: 19098026
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A powerful Bayesian meta-analysis method to integrate multiple gene set enrichment studies.
    Chen M; Zang M; Wang X; Xiao G
    Bioinformatics; 2013 Apr; 29(7):862-9. PubMed ID: 23418184
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.
    Lai Y; Zhang F; Nayak TK; Modarres R; Lee NH; McCaffrey TA
    BMC Genomics; 2014; 15 Suppl 1(Suppl 1):S6. PubMed ID: 24564564
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A novel bi-level meta-analysis approach: applied to biological pathway analysis.
    Nguyen T; Tagett R; Donato M; Mitrea C; Draghici S
    Bioinformatics; 2016 Feb; 32(3):409-16. PubMed ID: 26471455
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Nonparametric methods for identifying differentially expressed genes in microarray data.
    Troyanskaya OG; Garber ME; Brown PO; Botstein D; Altman RB
    Bioinformatics; 2002 Nov; 18(11):1454-61. PubMed ID: 12424116
    [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. Meta-analysis of cancer gene-profiling data.
    Yang X; Sun X
    Methods Mol Biol; 2010; 576():409-26. PubMed ID: 19882274
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Identifying periodically expressed transcripts in microarray time series data.
    Wichert S; Fokianos K; Strimmer K
    Bioinformatics; 2004 Jan; 20(1):5-20. PubMed ID: 14693803
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Covariance thresholding to detect differentially co-expressed genes from microarray gene expression data.
    Oh M; Kim K; Sun H
    J Bioinform Comput Biol; 2020 Feb; 18(1):2050002. PubMed ID: 32336254
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A flexible two-stage procedure for identifying gene sets that are differentially expressed.
    Heller R; Manduchi E; Grant GR; Ewens WJ
    Bioinformatics; 2009 Apr; 25(8):1019-25. PubMed ID: 19213738
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prior biological knowledge-based approaches for the analysis of genome-wide expression profiles using gene sets and pathways.
    Wu MC; Lin X
    Stat Methods Med Res; 2009 Dec; 18(6):577-93. PubMed ID: 20048386
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. CoGA: An R Package to Identify Differentially Co-Expressed Gene Sets by Analyzing the Graph Spectra.
    Santos Sde S; Galatro TF; Watanabe RA; Oba-Shinjo SM; Nagahashi Marie SK; Fujita A
    PLoS One; 2015; 10(8):e0135831. PubMed ID: 26313749
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.