Journal of Medical Systems

, Volume 30, Issue 1, pp 39–44 | Cite as

Computational Approaches for Predicting Protein–Protein Interactions: A Survey

Research Article


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.


Protein–protein interactions Yeast two-hybrid Computational prediction 


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Copyright information

© Springer Science + Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Department of Computer ScienceWayne State University Detroit

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