Standards in gene expression microarray experiments

被引：13
|
作者：
Salit, Marc [1 ]
机构：
[1] Natl Inst Stand & Technol, Chem Sci & Technol Lab, Gaithersburg, MD 20899 USA
来源：
DNA MICROARRAYS, PART B: DATABASES AND STATISTICS | 2006年 / 411卷
关键词：
D O I：
10.1016/S0076-6879(06)11005-8
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
The use of standards in gene expression measurements with DNA microarrays is ubiquitous-they just are not yet the kind of standards that have yielded microarray gene expression profiles that can be readily compared across different studies and different laboratories. They also are not yet enabling microarray measurements of the known, verifiable quality needed so they can be used with confidence in genomic medicine in regulated environments.
引用
收藏
页码：63 / 78
页数：16
相关论文
共 50 条
  • [31] Universal human, mouse and rat reference RNA as standards for microarray experiments
    Novoradovskaya, N
    Perou, C
    Whitfield, M
    Basehore, S
    Pesich, R
    Aprelikova, O
    Fero, M
    Brown, PO
    Botstein, D
    Braman, J
    MOLECULAR BIOLOGY OF THE CELL, 2002, 13 : 241A - 241A
  • [32] Time-resolved gene expression experiments by using a single-cell electroporation microarray
    Santoni, Lisbet
    Bersani, Cinzia
    Borgo, Mauro
    Bandiera, Leonardo
    Cellere, Giorgio
    Vassanelli, Stefano
    Chiaramello, Samuele
    JOURNAL OF BIOTECHNOLOGY, 2007, 131 (02) : S51 - S51
  • [33] Using linear-bilinear models for studying gene expression × treatment interaction in microarray experiments
    Jose Crossa
    Juan Burgueño
    Daphne Autran
    Jean-Philippe Vielle-Calzada
    Paul L. Cornelius
    Normand Garcia
    Fabio Salamanca
    Diego Arenas
    Journal of Agricultural, Biological, and Environmental Statistics, 2005, 10 : 337 - 353
  • [34] 'The 39 steps' in gene expression profiling:: critical issues and proposed best practices for microarray experiments
    Imbeaud, S
    Auffray, C
    DRUG DISCOVERY TODAY, 2005, 10 (17) : 1175 - 1182
  • [35] Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
    Gao, X
    Song, PXK
    BMC BIOINFORMATICS, 2005, 6 (1)
  • [36] AtCAST, a Tool for Exploring Gene Expression Similarities among DNA Microarray Experiments Using Networks
    Sasaki, Eriko
    Takahashi, Chitose
    Asami, Tadao
    Shimada, Yukihisa
    PLANT AND CELL PHYSIOLOGY, 2011, 52 (01) : 169 - 180
  • [37] Mixture of linear mixed models for clustering gene expression profiles from repeated microarray experiments
    Celeux, G
    Martin, O
    Lavergne, C
    STATISTICAL MODELLING, 2005, 5 (03) : 243 - 267
  • [38] Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
    Xin Gao
    Peter XK Song
    BMC Bioinformatics, 6
  • [39] Analysis of microarray gene expression data
    Pham, Tuan D.
    Wells, Christine
    Crane, Denis I.
    CURRENT BIOINFORMATICS, 2006, 1 (01) : 37 - 53
  • [40] Microarray studies of gene expression in fish
    Douglas, Susan E.
    OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY, 2006, 10 (04) : 474 - 489
12345