BMC Genomics 2008, 9:461 http://www.biomedcentral.com/1471-2164/9/461 itives or that involve co-expressed genes. The results page also includes a link for downloading the interactions in formats that can then be uploaded into network analysis programs. Finally, a link is included that will generate a summary table showing the number of interactions for the selected genes in each of the interaction datasets, including those not originally searched. The summary table also includes a button that automatically opens the IM Browser applet to generate a graphical map of the interactions (see below). DroID can be accessed via two different dynamic inter- faces that allow an interaction network to be explored as a graph where nodes represent genes or proteins and edges connecting the nodes represent interactions. View- ing an interaction map in this way places each gene and interaction into the context of other interactions and facil- itates biological insights that are not possible from simple lists of interactions. The first interface is a plug-in (Figure 1C) that allows DroID to be accessed through the power- ful network visualization and analysis program, Cyto- scape [49]. The second interface is IM Browser (Figure 1D), a program originally designed to access an earlier version of DroID and other interaction databases [28]. IM Browser runs as a java applet and allows advanced queries and dynamic graphing of search results. While a complete description of IM Browser capabilities is beyond the scope of this paper, a few features are worth noting here. First, the program easily accommodates new types of interac- tion data and dynamically enables all node and edge information to be used in searches and filtering. This fea- ture is important as new techniques for detecting interac- tions are needed and continue to emerge, and each new technique has its own type of data. Second, interaction maps can be edited and saved to the user's local computer, and local datasets can be loaded into the program to allow the user to view and analyze their own interactions in the context of DroID data. Finally, a new feature of IM Browser allows maps to be filtered based on gene expres- sion data or confidence scores. The constraint is imple- mented as a dynamic filter that can be applied to an existing interaction map. As new gene expression data becomes available, and eventually protein expression data is collected from proteomics studies, an increasingly fruit- ful way to view interaction maps will be in the context of specific temporal and spatial expression patterns. Conclusion DroID is a comprehensive interactions database designed specifically for Drosophila melanogaster. The database cur- rently covers more Drosophila genes and interactions than any other single database and is periodically updated. Because it is an organism-specific database, it readily includes potentially conserved interactions found in other organisms by mapping them to Drosophila genes. The database also includes comprehensive gene information, including Drosophila-specific information, which can be used to search for and filter interactions and to analyze gene networks. DroID includes gene expression data, both as expression profiles and as correlation values, to help researchers link together genes that may function together in specific biological processes. Finally, DroID assigns updateable confidence scores to every physical interaction to help focus studies on biologically relevant links. Com- bined with three user interfaces, DroID should provide a valuable resource for studying Drosophila systems. Availability and requirements DroID is freely available for non-commercial use. Any modern web browser can access the DroID home page at http://www.droidb.org/. A web browser with an installed Java Virtual Machine can access IM Browser from the DroID home page or from a list of found interactions. Cytoscape [49] enables installation and usage of the DroID plugin for Cytoscape. Authors' contributions RLF conceptualized the project. JY and RLF designed and built the database. JY performed data analysis. SP and RLF designed and built the interfaces. GL compiled a previous version of the database. RLF and JY wrote the draft. All authors tested the database and interfaces. Acknowledgements We thank Jodi R. Parrish, George G. Roberts III, and Stephen Guest for helpful comments on the manuscript. This work was supported in part through grants from the National Institutes of Health (HG001536) and the National Center for Research Resources (RR18327). References 1. Shoemaker BA, Panchenko AR: Deciphering protein-protein interactions. Part I. Experimental techniques and databases. PLoS Comput Biol 2007, 3(3):e42. 2. Fields S, Song O: A Novel Genetic System to Detect Protein- Protein Interactions. Nature 1989, 340(6230):245-246. 3. Parrish JR, Gulyas KD, Finley RL Jr: Yeast two-hybrid contribu- tions to interactome mapping. Curr Opin Biotechnol 2006, 17(4):387-393. 4. Fields S: High-throughput two-hybrid analysis. The promise and the peril. Febs J 2005, 272(21):5391-5399. 5. Vidal M: Interactome modeling. FEBS Lett 2005, 579(8):1834-1838. 6. Gavin AC, Superti-Furga G: Protein complexes and proteome organization from yeast to man. Curr Opin Chem Biol 2003, 7(1):21-27. 7. Gingras AC, Aebersold R, Raught B: Advances in protein com- plex analysis using mass spectrometry. J Physiol 2005, 563(Pt 1):11-21. 8. Deplancke B, Mukhopadhyay A, Ao W, Elewa AM, Grove CA, Mar- tinez NJ, Sequerra R, Doucette-Stamm L, Reece-Hoyes JS, Hope IA, et al.: A gene-centered C. elegans protein-DNA interaction network. Cell 2006, 125(6):1193-1205. 9. Lee TI, Rinaldi NJ, Robert F, Odom DT, Bar-Joseph Z, Gerber GK, Hannett NM, Harbison CT, Thompson CM, Simon I, et al.: Tran- scriptional regulatory networks in Saccharomyces cerevi- siae. Science 2002, 298(5594):799-804. 10. Mukherjee S, Berger MF, Jona G, Wang XS, Muzzey D, Snyder M, Young RA, Bulyk ML: Rapid analysis of the DNA-binding specif- Page 8 of 9 (page number not for citation purposes)