Oligonucleotide microarray identification of Bacillus anthracis strains using support vector machines

Michael Doran*, D. S. Raicu, J. D. Furst, R. Settimi, M. Schipma, D. P. Chandler

*Corresponding author for this work

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

The capability of a custom microarray to discriminate between closely related DNA samples is demonstrated using a set of Bacillus anthracis strains. The microarray was developed as a universal fingerprint device consisting of 390 genome-independent 9mer probes. The genomes of B. anthracis strains are monomorphic and therefore, typically difficult to distinguish using conventional molecular biology tools or microarray data clustering techniques. Using support vector machines (SVMs) as a supervised learning technique, we show that a low-density fingerprint microarray contains enough information to discriminate between B. anthracis strains with 90% sensitivity using a reference library constructed from six replicate arrays and three replicates for new isolates.

Original languageEnglish (US)
Pages (from-to)487-492
Number of pages6
JournalBioinformatics
Volume23
Issue number4
DOIs
StatePublished - Feb 15 2007

ASJC Scopus subject areas

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

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