English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Oligonucleotide microarrays are an informative tool to elucidate gene regulatory networks. In order for gene expression levels to be comparable across microarrays, normalization procedures have to be invoked. A large number of methods have been described to correct for systematic biases in microarray experiments. The performance of these methods has been tested only to a limited extend. Here, we evaluate two different types of microarray analyses: (i) the same gene in replicate samples and (ii) different, but co-expressed genes in the same sample. The reliability of the latter analysis needs to be determined for the analysis of regulatory networks and our report is the first attempt to evaluate for the accuracy of different microarray normalization methods in this respect. Consistent with previous results we observed a large effect of the normalization method on the outcome of the expression analyses. Our analyses indicate that different normalization methods should be performed depending on whether a study is aiming to detect differential gene expression between independent samples or whether co-expressed genes should be identified. We make recommendations about the most appropriate method to use.

Comparison of algorithms for the analysis of Affymetrix microarray data as evaluated by co-expression of genes in known operons