Finding class C GPCR subtype-discriminating N-grams through feature selection

Caroline König, René Alquézar, Alfredo Vellido, Jesús Giraldo

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)89-96
Number of pages8
JournalAdvances in Intelligent Systems and Computing
Issue numberAISC
Publication statusPublished - 2014


  • Feature selection
  • G-Protein coupled receptors
  • n-grams
  • Pharmaco-proteomics
  • Support vector machines


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