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Journal Abstract Search

205 related items for PubMed ID: 20184770

  • 1. SplicerAV: a tool for mining microarray expression data for changes in RNA processing.
    Robinson TJ, Dinan MA, Dewhirst M, Garcia-Blanco MA, Pearson JL.
    BMC Bioinformatics; 2010 Feb 25; 11():108. PubMed ID: 20184770
    [Abstract] [Full Text] [Related]

  • 2. Gene expression and isoform variation analysis using Affymetrix Exon Arrays.
    Bemmo A, Benovoy D, Kwan T, Gaffney DJ, Jensen RV, Majewski J.
    BMC Genomics; 2008 Nov 07; 9():529. PubMed ID: 18990248
    [Abstract] [Full Text] [Related]

  • 3. The effect of oligonucleotide microarray data pre-processing on the analysis of patient-cohort studies.
    Verhaak RG, Staal FJ, Valk PJ, Lowenberg B, Reinders MJ, de Ridder D.
    BMC Bioinformatics; 2006 Mar 02; 7():105. PubMed ID: 16512908
    [Abstract] [Full Text] [Related]

  • 4. SplicerEX: a tool for the automated detection and classification of mRNA changes from conventional and splice-sensitive microarray expression data.
    Robinson TJ, Forte E, Salinas RE, Puri S, Marengo M, Garcia-Blanco MA, Luftig MA.
    RNA; 2012 Aug 02; 18(8):1435-45. PubMed ID: 22736799
    [Abstract] [Full Text] [Related]

  • 5. Comparison of Affymetrix Gene Array with the Exon Array shows potential application for detection of transcript isoform variation.
    Ha KCh, Coulombe-Huntington J, Majewski J.
    BMC Genomics; 2009 Nov 12; 10():519. PubMed ID: 19909511
    [Abstract] [Full Text] [Related]

  • 6. Robust multi-tissue gene panel for cancer detection.
    Irgon J, Huang CC, Zhang Y, Talantov D, Bhanot G, Szalma S.
    BMC Cancer; 2010 Jun 22; 10():319. PubMed ID: 20569444
    [Abstract] [Full Text] [Related]

  • 7. Transcript and protein expression profiles of the NCI-60 cancer cell panel: an integromic microarray study.
    Shankavaram UT, Reinhold WC, Nishizuka S, Major S, Morita D, Chary KK, Reimers MA, Scherf U, Kahn A, Dolginow D, Cossman J, Kaldjian EP, Scudiero DA, Petricoin E, Liotta L, Lee JK, Weinstein JN.
    Mol Cancer Ther; 2007 Mar 22; 6(3):820-32. PubMed ID: 17339364
    [Abstract] [Full Text] [Related]

  • 8. 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 Mar 22; 17(5):2519-25. PubMed ID: 27268623
    [Abstract] [Full Text] [Related]

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  • 10. A large-scale comparative study of isoform expressions measured on four platforms.
    Zhang W, Petegrosso R, Chang JW, Sun J, Yong J, Chien J, Kuang R.
    BMC Genomics; 2020 Mar 30; 21(1):272. PubMed ID: 32228441
    [Abstract] [Full Text] [Related]

  • 11. puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.
    Liu X, Gao Z, Zhang L, Rattray M.
    BMC Bioinformatics; 2013 Feb 05; 14():39. PubMed ID: 23379655
    [Abstract] [Full Text] [Related]

  • 12. TIPMaP: a web server to establish transcript isoform profiles from reliable microarray probes.
    Chitturi N, Balagannavar G, Chandrashekar DS, Abinaya S, Srini VS, Acharya KK.
    BMC Genomics; 2013 Dec 27; 14():922. PubMed ID: 24373374
    [Abstract] [Full Text] [Related]

  • 13. Finding temporal gene expression patterns for translational research.
    Tusch G, Tolea O, Kutsumi Y, Sam VK, Mamidi L.
    Stud Health Technol Inform; 2013 Dec 27; 192():1173. PubMed ID: 23920947
    [Abstract] [Full Text] [Related]

  • 14. AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data.
    Lu G, Nguyen TV, Xia Y, Fromm M.
    BMC Bioinformatics; 2006 Dec 12; 7 Suppl 4(Suppl 4):S26. PubMed ID: 17217519
    [Abstract] [Full Text] [Related]

  • 15. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation.
    Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L.
    Nat Biotechnol; 2010 May 12; 28(5):511-5. PubMed ID: 20436464
    [Abstract] [Full Text] [Related]

  • 16. Methods for evaluating gene expression from Affymetrix microarray datasets.
    Jiang N, Leach LJ, Hu X, Potokina E, Jia T, Druka A, Waugh R, Kearsey MJ, Luo ZW.
    BMC Bioinformatics; 2008 Jun 17; 9():284. PubMed ID: 18559105
    [Abstract] [Full Text] [Related]

  • 17. Common Subcluster Mining in Microarray Data for Molecular Biomarker Discovery.
    Sadhu A, Bhattacharyya B.
    Interdiscip Sci; 2019 Sep 17; 11(3):348-359. PubMed ID: 29022249
    [Abstract] [Full Text] [Related]

  • 18. Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.
    Guzzi PH, Cannataro M.
    Comput Methods Programs Biomed; 2013 Aug 17; 111(2):402-9. PubMed ID: 23731720
    [Abstract] [Full Text] [Related]

  • 19. Framework for reanalysis of publicly available Affymetrix® GeneChip® data sets based on functional regions of interest.
    Saka E, Harrison BJ, West K, Petruska JC, Rouchka EC.
    BMC Genomics; 2017 Dec 06; 18(Suppl 10):875. PubMed ID: 29244006
    [Abstract] [Full Text] [Related]

  • 20. Comparing gene discovery from Affymetrix GeneChip microarrays and Clontech PCR-select cDNA subtraction: a case study.
    Cao W, Epstein C, Liu H, DeLoughery C, Ge N, Lin J, Diao R, Cao H, Long F, Zhang X, Chen Y, Wright PS, Busch S, Wenck M, Wong K, Saltzman AG, Tang Z, Liu L, Zilberstein A.
    BMC Genomics; 2004 Apr 27; 5(1):26. PubMed ID: 15113399
    [Abstract] [Full Text] [Related]

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