What is IID?
IID (Integrated Interaction Database) is an on-line database of known and predicted eukaryotic protein-protein interactions, in 30 tissues of model organisms and humans.
What makes IID different from other interaction databases?
- IID is the only database with tissue specific PPIs in model organisms and human.
- Users can input proteins from one organism (or more) and get tissue-specific interactions in multiple specified organisms. IID can map input proteins to orthologs and search for their interactions.
- IID integrates 3 types of extensive PPI networks: experimentally detected PPIs from 9 major databases (BioGRID, IntAct, I2D, MINT, InnateDB, DIP, HPRD, BIND, BCI), orthologous PPIs, and high-confidence computationally predicted PPI from recent studies.
What model organism data is in IID?
IID includes data for S. cerevisiae (yeast), C. elegans (worm), D. melonogaster (fly), R. norvegicus (rat), M. musculus (mouse), and H. sapiens (human). For complete information on data sources and references, refer to the statistics page.
Example applications of IID
- Let's assume a researcher is well accustomed to the role of EGFR in lung cancer and the effect of EGFR mutations on several pathways as well as interactions. As lung cancer frequently metastasize to brain, the scientist might want to understand the similarity between the two tissues, starting from the EGFR network, to see if there are overlapping interactions that would be a starting point for subsequent studies. A search for human EGFR in any tissue gives back 1593 interactions. When restricting the search to lung and brain, it is possible to see that there are 1292 interactions in common between the two tissues for the same gene.
- The path that leads a drug from bench to bed is quite long and complex, including several steps that are meant to filter out bad (or useless) drugs and to assure the safety of the same in clinical use. This process starts from testing the drug in human cell lines and in in vivo models (most frequently mice). A researcher involved in this type of study might have tested the drug on cell lines and know which are the targets of the compound and which pathways are disrupted and he might want to see what happens to the same when he administer the same drug to a mouse. To this aim, the researcher might search for the genes of interest in IID, select human and mouse and retrieve interactions that are conserved in the two species. Following example 1 search, if we input EGFR and select human and mouse species we get the same 1593 interactions for human and 989 for mouse. If we do select " Return only interactions conserved across all selected species" we actually get only the intersection, consisting of 985 interactions for both.