PRIN, a Predicted Rice Interactome Network, presents a computational approach to predict the protein-protein interactions in Oryza sativa. PRIN is based on a sophisticated method known as interologs, and the genome information such as GO annotation, subcellular localization information and the gene expression data are added to validate network and get biological significant network properties as well.
Protein-protein interactions data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fruitfly (Drosophila melanogaster), human (Homo sapiens), Escherichia coli K12 and Arabidopsis thaliana. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. According to the comparison with small experiment interactome and random interactome, PRIN shows satisfactory tendency in co-GO annotation, co-localization and co-expression, and it is reliable for perspective study in rice functional biology and systems biology.