Systematic analysis snake neurotoxins' functional classification using a data warehousing approach

Joyce Phui Yee Siew, Asif M. Khan, Paul T.J. Tan, Judice L.Y. Koh, Seng Hong Seah, Chuay Yeng Koo, Siaw Ching Chai, Arunmozhiarasi Armugam, Vladimir Brusic, Kandiah Jeyaseelan

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Motivation: Sequence annotations, functional and structural data on snake venom neurotoxins (svNTXs) are scattered across multiple databases and literature sources. Sequence annotations and structural data are available in the public molecular databases, while functional data are almost exclusively available in the published articles. There is a need for a specialized svNTXs database that contains NTX entries, which are organized, well annotated and classified in a systematic manner. Results: We have systematically analyzed svNTXs and classified them using structure-function groups based on their structural, functional and phylogenetic properties. Using conserved motifs in each phylogenetic group, we built an intelligent module for the prediction of structural and functional properties of unknown NTXs. We also developed an annotation tool to aid the functional prediction of newly identified NTXs as an additional resource for the venom research community.

Original languageEnglish
Pages (from-to)3466-3480
Number of pages15
JournalBioinformatics
Volume20
Issue number18
DOIs
Publication statusPublished - Dec 12 2004

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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