An intelligent agents architecture for DNA-microarray data integration

DNA microarray is a highly-parallel methodology to screen genome samples for the expression of particular DNA sequences [1]. To gather information about gene expression is a much more difficult task than DNA sequence, because gene expression is a dynamic process dependent on many factors. The knowledge of the ORFs (Open Reading Framework) for a certain organism opens the possibility to globally study the expression of these genes under chosen circumstances. By using DNA-microarray methodology, the investigator gets a global picture of the genes expression under study. Since experimental data are disseminated in a myriad of different databases that are duplicated in several repositories, the experimental data integration and clustering imply the exploration of a sites network from which the investigator can integrate (select and cluster) data of interest. The authors propose to adopt an intelligent agent architecture as communication and coordination tool among distributed sites. In this paper an intelligent agent architecture will be applied to the case of the expression of yeast genome, where several microarray hybridization experimental datasets are available [9].