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Using Machine Learning Techniques and Genomic/Proteomic Information from Known Databases for PPI Prediction

  • J. M. Urquiza
  • I. Rojas
  • H. Pomares
  • L. J. Herrera
  • J. P. Florido
  • F. Ortuño
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 93)

Abstract

In current Proteomics, prediction of protein-protein interactions (PPI) is a crucial aim as these interactions take part in most essential biological processes. In this paper, we propose a new approach to PPI dataset processing based on the extraction information from well-known databases and the application of data mining techniques. This approach will provide very accurate Support Vector Machine models, trained using high-confidence positive and negative examples. Finally, our proposed model has been validated using experimental, computational and literature-collected datasets.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • J. M. Urquiza
    • 1
  • I. Rojas
    • 1
  • H. Pomares
    • 1
  • L. J. Herrera
    • 1
  • J. P. Florido
    • 1
  • F. Ortuño
    • 1
  1. 1.Dept of Computer Architecture and Computer TechnologyUniversity of GranadaSpain

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