Abstract

Discovery of the protein interactions that take place within a cell can provide a starting point for understanding biological regulatory pathways. Global interaction patterns among proteins, for example, can suggest new drug targets and aid the design of new drugs by providing a clearer picture of the biological pathways in the neighborhoods of the drug targets. High-throughput experimental screens have been developed to detect protein-protein interactions, however, they show high rates of errors in terms of false positives and false negatives. Many computational approaches have been proposed to tackle the problem of protein-protein interaction prediction. They range from comparative genomics based methods to data integration based approaches. Challenging properties of protein-protein interaction data have to be addressed appropriately before a higher quality interaction map with better coverage can be achieved. This paper presents a survey of major works in computational prediction of protein-protein interactions, explaining their assumptions, main ideas, and limitations.