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Finding Class C GPCR Subtype-Discriminating N-grams through Feature Selection

  • Caroline KönigEmail author
  • René Alquézar
  • Alfredo Vellido
  • Jesús Giraldo
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 294)

Abstract

G protein-coupled receptors (GPCRs) are a large and heterogeneous superfamily of receptors that are key cell players for their role as extracellular signal transmitters. Class C GPCRs, in particular, are of great interest in pharmacology. The lack of knowledge about their full 3-D structure prompts the use of their primary amino acid sequences for the construction of robust classifiers, capable of discriminating their different subtypes. In this paper, we describe the use of feature selection techniques to build Support Vector Machine (SVM)-based classification models from selected receptor subsequences described as n-grams. We show that this approach to classification is useful for finding class C GPCR subtype-specific motifs.

Keywords

G-Protein coupled receptors pharmaco-proteomics feature selection n-grams support vector machines 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Caroline König
    • 1
    Email author
  • René Alquézar
    • 1
    • 2
  • Alfredo Vellido
    • 1
    • 3
  • Jesús Giraldo
    • 4
  1. 1.Departament de Llenguatges i Sistemes InformàticsUniv. Politècnica de Catalunya, BarcelonaTechBarcelonaSpain
  2. 2.Institut de Robòtica i Informàtica Industrial, CSIC-UPCBarcelonaSpain
  3. 3.Centro de Investigación Biomédica en Red en BioingenieríaBiomateriales y Nanomedicina (CIBER-BBN)Cerdanyola del VallèsSpain
  4. 4.Institut de Neurociències - Unitat de Bioestadìstica, Univ. Autònoma de BarcelonaCerdanyola del VallèsSpain

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