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Bioinformatics Advance Access published online on January 3, 2007
Bioinformatics, doi:10.1093/bioinformatics/btl626
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received October 1, 2006
Revised November 30, 2006
Accepted December 4, 2006

Article

Oligonucleotide microarray identification of Bacillus anthracis strains using support vector machines

M. Doran 1 *, D. S. Raicu 1, J. D. Furst 1, R. Settimi 1, M. Schipma 2, and D. P. Chandler 3

1 Intelligent Multimedia Processing Laboratory, School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA
2 Biodetection Technologies, Argonne National Laboratory, Chicago, USA
3 Biodetection Technologies, Argonne National Laboratory, Chicago, USA; Present address = Akonni Biosystems, Inc., Frederick, MD, USA

* To whom correspondence should be addressed.
M. Doran, E-mail: doran_michael{at}msn.com


  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 9-mer 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 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 6 replicate arrays and 3 replicates for new isolates.

Associate Editor: Jonathan Wren
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