Literature DB >> 12495124

DNA microarray experiments: biological and technological aspects.

Danh V Nguyen1, A Bulak Arpat, Naisyin Wang, Raymond J Carroll.   

Abstract

DNA microarray technologies, such as cDNA and oligonucleotide microarrays, promise to revolutionize biological research and further our understanding of biological processes. Due to the complex nature and sheer amount of data produced from microarray experiments, biologists have sought the collaboration of experts in the analytical sciences, including statisticians, among others. However, the biological and technical intricacies of microarray experiments are not easily accessible to analytical experts. One aim for this review is to provide a bridge to some of the relevant biological and technical aspects involved in microarray experiments. While there is already a large literature on the broad applications of the technology, basic research on the technology itself and studies to understand process variation remain in their infancy. We emphasize the importance of basic research in DNA array technologies to improve the reliability of future experiments.

Mesh:

Year:  2002        PMID: 12495124     DOI: 10.1111/j.0006-341x.2002.00701.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  26 in total

1.  A mixture model approach to detecting differentially expressed genes with microarray data.

Authors:  Wei Pan; Jizhen Lin; Chap T Le
Journal:  Funct Integr Genomics       Date:  2003-07-01       Impact factor: 3.410

2.  Combining gene expression and molecular marker information for mapping complex trait genes: a simulation study.

Authors:  Miguel Pérez-Enciso; Miguel A Toro; Michel Tenenhaus; Daniel Gianola
Journal:  Genetics       Date:  2003-08       Impact factor: 4.562

3.  Assessment of reliability of microarray data and estimation of signal thresholds using mixture modeling.

Authors:  Musa H Asyali; Mohamed M Shoukri; Omer Demirkaya; Khalid S A Khabar
Journal:  Nucleic Acids Res       Date:  2004-04-27       Impact factor: 16.971

4.  Quantifying the relationship between gene expressions and trait values in general pedigrees.

Authors:  Yan Lu; Peng-Yuan Liu; Yong-Jun Liu; Fu-Hua Xu; Hong-Wen Deng
Journal:  Genetics       Date:  2004-09-15       Impact factor: 4.562

Review 5.  Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology.

Authors:  Wenjiang J Fu; Arnold J Stromberg; Kert Viele; Raymond J Carroll; Guoyao Wu
Journal:  J Nutr Biochem       Date:  2010-03-16       Impact factor: 6.048

6.  Nonparametric variance estimation in the analysis of microarray data: a measurement error approach.

Authors:  Raymond J Carroll; Yuedong Wang
Journal:  Biometrika       Date:  2008       Impact factor: 2.445

Review 7.  Nutrigenomics and personalized diets: What will they mean for food?

Authors:  J Bruce German; Angela M Zivkovic; David C Dallas; Jennifer T Smilowitz
Journal:  Annu Rev Food Sci Technol       Date:  2011

8.  A discussion concerning the inclusion of variety effect when analysis of variance is used to detect differentially expressed genes.

Authors:  Guri Feten; Are Halvor Aastveit; Lars Snipen; Trygve Almøy
Journal:  Gene Regul Syst Bio       Date:  2007-06-15

9.  Variability of DNA microarray gene expression profiles in cultured rat primary hepatocytes.

Authors:  Jun Xu; Xutao Deng; Victor Chan; Nancy Kelley-Loughnane; Brent W Harker; Leming Shi; Saber M Hussain; John M Frazier; Charles Wang
Journal:  Gene Regul Syst Bio       Date:  2007-11-18

10.  Evaluation of fecal mRNA reproducibility via a marginal transformed mixture modeling approach.

Authors:  Nysia I George; Joanne R Lupton; Nancy D Turner; Robert S Chapkin; Laurie A Davidson; Naisyin Wang
Journal:  BMC Bioinformatics       Date:  2010-01-07       Impact factor: 3.169

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