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Computational Prediction of Protein-Protein Interactions

  • Anton J. Enright
  • Lucy Skrabanek
  • Gary D. Bader

Abstract

One of the current goals of proteomics is to map the protein interaction networks of a large number of model organisms (1). Protein-protein interaction information allows the function of a protein to be defined by its position in a complex web of interacting proteins. Access to such information will greatly aid biological research and poten- tially make the discovery of novel drug targets much easier. Previously, the detection of protein-protein interactions was limited to labor-intensive experimental techniques such as co-immunoprecipitation or affinity chromatography. High-throughput experi- mental techniques such as yeast two-hybrid and mass spectrometry have now also become available for large-scale detection of protein interactions. These methods, how- ever, may not be generally applicable to all proteins in all organisms, and may also be prone to systematic error. Recently, a number of complementary computational approaches have been developed for the large-scale prediction of protein-protein inter- actions based on protein sequence, structure, and evolutionary relationships in com- plete genomes.

Keywords

Phylogenetic Profile Multiple Genome Layout Algorithm Orthology Assignment Protein Interaction Site 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Humana Press Inc., Totowa, NJ 2005

Authors and Affiliations

  • Anton J. Enright
    • 1
  • Lucy Skrabanek
    • 2
  • Gary D. Bader
    • 1
  1. 1.Computational Biology CenterMemorial Sloan-Kettering Cancer CenterNew York
  2. 2.Department of Physiology and Biophysics and Institute for Computational BiomedicineWeill Medical College of Cornell UniversityNew York

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