title: Data mining for protein-protein interactions in invertebrate model organisms.
abstract: Well-annotated genome databases are available for many invertebrate species, notably the fruitfly, Drosophila melanogaster, and the nematode, Caenorhabditis elegans. An adequate interpretation of this information at the biological level requires the exploration of the interactions between the gene products. Knowledge of protein interactions and the components of cell signalling pathways in the fly and worm are particularly valuable as hypotheses can be rapidly tested using the powerful genetic toolkits available. Invertebrates offer additional experimental advantages when attempting to characterise protein-protein interactions (PPIs). Their relatively small genome size compared to mammals helps to reduce missed interactions due to redundancy, and their function can be addressed using forward (mutants) and reverse (RNA interference) genetics. However, the researcher looking for evidence of PPIs for a protein of interest is faced with the challenge of extracting interaction data from sources that are highly varied, such as the results of microarray experiments in the unstructured text of research papers. This challenge is greatly reduced by a range of public databases of curated information, as well as publicly available, enhanced search engines, which can provide either direct experimental evidence for a PPI, or valuable clues for generating new hypotheses.
authors.affiliation: MRC Functional Genetics Unit, Department of Human Anatomy and Genetics, University of Oxford, South Parks Road, Oxford, UK. steven.buckingham@anat.ox.ac.uk
authors.forename: Steven D
authors.initials: SD
authors.lastname: Buckingham
mesh_terms: D000818:Animals; D030562:Databases, Protein; D016247:Information Storage and Retrieval / Q000379:methods*; D007448:Invertebrates / Q000502:physiology*; D025941:Protein Interaction Mapping; D011506:Proteins / Q000378:metabolism*; D040901:Proteomics
chemical_list: D011506:Proteins