The Gene Ontology (GO), which was first published in the year 2000 (1), introduced the concept of associating a collection of genes with a functional biological term in a systematic way. GO was needed because methods such as cDNA microarrays that measure mRNA expression at a global genome-wide scale produce lists of differentially expressed genes that are difficult to interpret. The creation of GO enabled the analysis of gene lists in the context of prior knowledge. Early tools such as FatiGO (2), BiNGO (3) and TermFinder (4) first realized this concept. Initially, most enrichment analyses of sets of differentially expressed genes, integrated with prior knowledge, were limited to either GO terms, or gene sets were projected onto known protein–protein interaction networks and signaling pathways. These include, for example, membership of genes in pathway databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) (5). Later on, other types of annotated gene sets for enrichment analysis emerged; for example, chromosome location of genes, computationally predicted targets of microRNAs and transcription factors, and gene modules identified computationally from large collections of
