Computational Approaches for Predicting Protein---Protein Interactions: A Survey

  • Authors:
  • Jingkai Yu;Farshad Fotouhi

  • Affiliations:
  • Department of Computer Science, Wayne State University Detroit;Department of Computer Science, Wayne State University Detroit

  • Venue:
  • Journal of Medical Systems
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

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.