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Selection of GO-Based Semantic Similarity Measures through AMDE for Predicting Protein-Protein Interactions

  • Anirban Mukhopadhyay
  • Moumita De
  • Ujjwal Maulik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7077)

Abstract

Protein-protein interactions (PPI) form the core part of the entire interatomic system for all the living elements. In this article, the role of different Gene Ontology(GO)-based semantic similarity measures in predicting PPIs have been explored. To find out a relevant subset of semantic similarity measures, a feature selection approach is developed with Angle Modulated Differential Evolution(AMDE), an improved binary differential evolution technique. In this feature selection approach, SVM classifier is used as a wrapper where different metrics like sensitivity, specificity accuracy and Area Under Curve (AUC) are measured to find the best performing feature subset. Results have been demonstrated for real-life PPI data of yeast.

Keywords

Protein-Protein Interaction GO-based protein similarity Angle Modulated Differential Evolution (AMDE) feature selection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Anirban Mukhopadhyay
    • 1
  • Moumita De
    • 1
  • Ujjwal Maulik
    • 2
  1. 1.Department of Computer Science and EngineeringUniversity of KalyaniKalyaniIndia
  2. 2.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia

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