The microarray gene annotations were reanalysed by Sigenae (Institut National de la Recherche Agronomique, Toulouse, France).
We acknowledge Jessica Alfoldi, Federica Di Palma, and Kerstin Lindblad-Toh at the Broad Institute for access to rabbit genome sequence data used to improve the microarray gene annotations.
We acknowledge Jessica Alfoldi, Federica Di Palma, and Kerstin Lindblad-Toh at the Broad Institute for access to the rabbit genome sequence data used to improve the microarray gene annotations in our study.
For each microarray platform, gene annotation was performed with the MADGene tool [ 70] (see also part 6 of the Additional File 3 for more details on this database).
Parameters of the tool are object type (two organisms, two individuals, two tissues, etc)., type of computational gene family inference, experimental meta-data, microarray platform, gene annotation level and genome build.
This may be due to technical differences such as concentration of interferons, microarray platform and gene annotation, but may also reflect cell-specific (professional immune vs non-immune) responses to IFN stimulation [54].
This paper analyzes correlation between the proximity of eukaryotic genes and their transcriptional expression pattern in the zebrafish (Danio rerio) genome using available microarray data and gene annotation.
Using public microarray datasets and gene annotation, we investigated, for the first time, the global gene expression patterns in the zebrafish genome.
As illustrated in Figure 1 we selected six microarray studies containing complete gene annotation and full information on phases and levels of expression of genes with an oscillating circadian pattern [5], [6], [15], [16], [17], [18].
Whereas there is a wealth of methods published to analyze microarray data together with gene annotation, little has been done to integrate experiment annotation related to experimental protocols and sample description.
