A three-layer multidatabase system for functional statistical analyses of microarray experiment results

New high-throughput technologies available for the post-genomic era, such as the microarrays, produce lists of hundreds of genes candidate regulated, or with particular expression profiles, in the conditions under study. These lists need to be biologically interpreted to gain a better knowledge of the pathophysiological phenomena involved. To this aim, several biological annotations are available within heterogeneous and widely distributed databases. Although numerous tools have been developed for annotating lists of genes, most of them do not provide methods for evaluating the relevance of the annotations provided, or for estimating the functional bias introduced by the gene set on the array used to identify the considered gene list. To reach this goal, we developed GFINDer, Genome Function INtegrated Discover, a Web-accessible three-layer multidatabase system that automatically provides large-scale lists of user-classified genes with functional profiles biologically characterizing the different gene classes in the list. GFINDer automatically retrieves annotations of several functional categories from different sources, identifies the categories enriched in each class of a user-classified gene list, and calculates statistical significance values for each category. It also enables to functionally classify genes according to user-selected criteria and to analyse the resulting classifications, aiding in better biologically interpreting microarray experiment results.