Third, when combining different microarray experiments, differences in mRNA extraction protocols, microarray platform and possibly normalization and summarization algorithms, add to the already large amount of unquantified heterogeneity amongst experimental conditions (Bammler et al., 2005; Tan et al., 2003).
In co-expression analysis one searches for genes that show a similar expression profile across numerous different microarray experiments, representing different environmental and stress conditions as well as developmental stages and tissue types.
This difference between Genevestigator and experimental data could be a consequence of different levels of detection in RT-PCR and microarray experiments or different experimental conditions.
Suppose that gene A is regulated by genes B and C, and that we want to determine the regulatory phrases, i.e. how A changes its expression due to the joint combinatorial changes of B and C. In order to do so, we need a set of microarray experiments in different conditions that have been already normalized and their background noise subtracted.
We assembled a set of 2005 yeast microarray experiments from different laboratories, platforms and experimental procedures (see materials and methods).
We illustrate the application of the methodology with gene expression data obtained from various microarray experiments with different conditions and diseases.
To test these hypotheses integrated analysis of a large number of gene expression microarray experiments from different forms of allergy was performed.
In the last years, enormous data has been generated with microarray experiments from different organisms, tissues and platforms under various experimental conditions.
Comparison of microarray experiments from different species targeted to the same developmental process offers the opportunity to compare gene expression patterns for a large number of genes.
Annotated information is required for data integration using matching identifiers, e.g. two microarray experiments on different platforms can be compared by mapping the vendor-specific probe ids to ENSEMBL gene ids.
