Literature DB >> 16354130

Microarray expression technology: from start to finish.

Gareth Elvidge1.   

Abstract

The recent introduction of new microarray expression technologies and the further development of established platforms ensure that the researcher is presented with a range of options for performing an experiment. Whilst this has opened up the possibilities for future applications, such as exon-specific arrays, increased sample throughput and 'chromatin immunoprecipitation (ChIP) on chip' experiments, the initial decision processes and experiment planning are made more difficult. This review will give an overview of the various technologies that are available to perform a microarray expression experiment, from the initial planning stages through to the final data analysis. Both practical aspects and data analysis options will be considered. The relative advantages and disadvantages will be discussed with insights provided for future directions of the technology.

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Year:  2006        PMID: 16354130     DOI: 10.2217/14622416.7.1.123

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  7 in total

Review 1.  The end of the microarray Tower of Babel: will universal standards lead the way?

Authors:  Ernest S Kawasaki
Journal:  J Biomol Tech       Date:  2006-07

Review 2.  Neuronal apoptosis revealed by genomic analysis: integrating gene expression profiles with functional information.

Authors:  Sebastiano Cavallaro
Journal:  Neuroinformatics       Date:  2007

3.  A perspective on DNA microarrays in pathology research and practice.

Authors:  Jonathan R Pollack
Journal:  Am J Pathol       Date:  2007-06-28       Impact factor: 4.307

Review 4.  A decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects.

Authors:  Bas J Wouters; Bob Löwenberg; Ruud Delwel
Journal:  Blood       Date:  2008-08-14       Impact factor: 22.113

5.  Empirical comparison of cross-platform normalization methods for gene expression data.

Authors:  Jason Rudy; Faramarz Valafar
Journal:  BMC Bioinformatics       Date:  2011-12-07       Impact factor: 3.169

6.  Differential analysis for high density tiling microarray data.

Authors:  Srinka Ghosh; Heather A Hirsch; Edward A Sekinger; Philipp Kapranov; Kevin Struhl; Thomas R Gingeras
Journal:  BMC Bioinformatics       Date:  2007-09-24       Impact factor: 3.169

7.  The Annotation, Mapping, Expression and Network (AMEN) suite of tools for molecular systems biology.

Authors:  Frédéric Chalmel; Michael Primig
Journal:  BMC Bioinformatics       Date:  2008-02-06       Impact factor: 3.169

  7 in total

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