Conotoxin protein classification using pairwise comparison and amino acid composition

Nazar Zaki, Fadi Sibai, Piers Campbell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Conotoxin classification could assist in the study of the structure function relationship of ion-channels and receptors as well as identifying potential therapeutics in the treatment of a wide variety of diseases such as schizophrenia, chronic pain, cardiovascular and bladder dysfunction. In this study, we introduce a novel method (Toxin-AAM) for conotoxin su-perfamily classification. Toxin-AAM incorporates evolutionary information using a powerful means of pairwise sequence comparison and amino acid composition knowledge. The combination of the sequential model and the discrete model has made the Toxin-AAM method exceptional in classifying conotoxin superfamily, when compared to other state-of-the-art techniques.

Original languageEnglish
Title of host publicationGenetic and Evolutionary Computation Conference, GECCO'11
Pages323-329
Number of pages7
DOIs
Publication statusPublished - 2011
Event13th Annual Genetic and Evolutionary Computation Conference, GECCO'11 - Dublin, Ireland
Duration: Jul 12 2011Jul 16 2011

Publication series

NameGenetic and Evolutionary Computation Conference, GECCO'11

Other

Other13th Annual Genetic and Evolutionary Computation Conference, GECCO'11
Country/TerritoryIreland
CityDublin
Period7/12/117/16/11

Keywords

  • Amino acid composition
  • Conotoxin classification
  • Pairwise alignment

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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