BMC Genomics 2008, 9:461 Table 1: DroID interaction datasets Data set Curagen yeast two-hybrid Finley yeast two-hybrid Hybrigenics yeast two-hybrid Other physical interactions* Human interologs Yeast interologs Worm interologs Genetic interactions http://www.biomedcentral.com/1471-2164/9/461 Number of Interactions Number of Genes 20182 2915 1856 897 40548 64407 2383 5350 6875 1225 1282 628 3996 2668 1432 1644 * Physical interactions that were detected outside the three large-scale yeast two-hybrid screens. The two-hybrid datasets are from references [30] for Curagen, [29] for Finley, and [31] for Hybrigenics. DroID contains the yeast two-hybrid interactions pub- lished in three major studies [29-31] in addition to unpublished interactions from an ongoing large-scale two-hybrid screening project [29,32]. Full experimental details as reported by the original publications are included. For Drosophila physical interactions not covered by the three large-scale yeast two-hybrid screens and for interactions of human, worm (C. elegans), and yeast pro- teins, raw data are downloaded from respective online databases. These databases include BioGRID [17], IntAct [16], and MINT [18], in addition to MIPS [33] for yeast and HPRD [20], PDZbase [34], and Reactome [21] for human. To enable periodic updates we established a pipe- line for entering data into DroID as follows. First, raw interaction data is parsed to ensure that it includes only physical protein-protein interactions. DroID obtains interactions annotated with at least one detection method that detects physical interactions (e.g., yeast two-hybrid, mass spectrometry, pull down, etc.). Second, we map genes to uniform identifiers for the four organisms uti- lized by DroID; that is, Flybase gene number (FBgn) for fly, Ensembl gene identifier (ENSG) for human, Worm- base gene identifier (WBGene) for worm, and ORF identi- fiers for yeast. For each interaction, DroID stores the original PubMed identifier (PMID), methods used in detecting it, and the databases reporting it. Finally, we map interactions collected from human, worm, and yeast to Drosophila interologs by orthology mapping using Inparanoid (currently at version 6) [35]. DroID also stores genetic interactions obtained from Flybase, each anno- tated by reference numbers that trace to original data sources. Aside from interologs, DroID currently does not include interactions based solely on computational pre- dictions, which may be found in other databases [36,37]. For example, the Fly-DPI database has Drosophila protein interactions predicted on the basis of domain pairs found in experimental PPI [37]. Gene attributes and gene expression data DroID includes a searchable gene attributes table popu- lated from periodically updated gene annotations availa- ble in Flybase [26]. Users can search for interactions involving specific genes by searching for gene names, sym- bols, synonyms, or gene identifiers. The gene attributes table also allows searches based on gene class, gene func- tion annotations based on gene ontology (GO) [38], and protein domains. The IM Browser interface [28] further extends this search ability by enabling a live search of Fly- base for genes based on additional attributes, including reference and phenotype. DroID also stores searchable gene expression data, which allows interaction data to be viewed and filtered in the context of gene expression patterns. DroID currently has two microarray-based gene expression datasets that can be used to constrain a search for interactions. One dataset includes genome-wide expression profiles over the course of embryogenesis in half-hour increments [39], and the other includes expression profiles for a developmental time course from early embryos through adults [40]. DroID can accommodate additional gene and protein expression data as they become available. Gene expression correlation Genes that are frequently co-expressed often function together in common processes (e.g., [41,42]). Thus, there is substantial value in knowing the level of co-expression for pairs of genes that interact. To facilitate co-expression analyses for Drosophila, we computed correlation values between pair-wise expression profiles derived from the Gene Expression Omnibus (GEO) database [43]. We downloaded all D. melanogaster gene expression datasets from GEO and computed linear Pearson correlations between pair-wise expression profiles within each dataset. We first removed datasets that have less than 5 samples (e.g., tissues, conditions, or time points) to avoid possible spurious strong correlations. This resulted in 49 genome- wide expression datasets with 844 combined samples. Multiple correlations for a pair of genes from different datasets were then combined to produce a final correla- tion value for a specific gene pair. The combination is done based on how many samples each dataset has. Intu- Page 4 of 9 (page number not for citation purposes)