Biological agent detection and identification using pattern recognition

Jerome J. Braun; Yan Glina; Nicholas Judson; Kevin D. Transue

doi:10.1117/12.605913

12 May 2005 Biological agent detection and identification using pattern recognition

Jerome J. Braun, Yan Glina, Nicholas Judson, Kevin D. Transue

Proceedings Volume 5795, Chemical and Biological Sensing VI; (2005) https://doi.org/10.1117/12.605913
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

This paper discusses a novel approach for the automatic identification of biological agents. The essence of the approach is a combination of gene expression, microarray-based sensing, information fusion, machine learning and pattern recognition. Integration of these elements is a distinguishing aspect of the approach, leading to a number of significant advantages. Amongst them are the applicability to various agent types including bacteria, viruses, toxins, and other, ability to operate without the knowledge of a pathogen's genome sequence and without the need for bioagent-speciific materials or reagents, and a high level of extensibility. Furthermore, the approach allows detection of uncatalogued agents, including emerging pathogens. The approach offers a promising avenue for automatic identification of biological agents for applications such as medical diagnostics, bioforensics, and biodefense.

Citation Download Citation

Jerome J. Braun, Yan Glina, Nicholas Judson, and Kevin D. Transue "Biological agent detection and identification using pattern recognition", Proc. SPIE 5795, Chemical and Biological Sensing VI, (12 May 2005); https://doi.org/10.1117/12.605913

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