Data mining published microarray experiments require that expression profiles are directly comparable. We performed linear global normalization on the data of 1967 Affymetrix U74av2 microarrays, i.e. the transcriptomes of >100 murine tissues or cell types. The mathematical transformation effectively nullifies inter-experimental or inter-laboratory differences between microarrays. The correctness of expression values was validated by quantitative RT-PCR. Using the database we analyze components of the aryl hydrocarbon receptor (AHR) signaling pathway in various tissues. We identified lineage and differentiation specific variant expression of AHR, ARNT, and HIF1alpha in the T-cell lineage and high expression of CYP1A1 in immature B cells and dendritic cells. Performing co-expression analysis we found unorthodox expression of the AHR in the absence of ARNT, particularly in stem cell populations, and can reject the hypothesis that ARNT2 takes over and is highly expressed when ARNT expression is low or absent. Furthermore the AHR shows no co-expression with any other transcript present on the chip. Analysis of differential gene expression under 308 conditions revealed 53 conditions under which the AHR is regulated, numerous conditions under which an intrinsic AHR action is modified as well as conditions activating the AHR even in the absence of known AHR ligands. Thus meta-analysis of published expression profiles is a powerful tool to gain novel insights into known and unknown systems.