MChip:  A Tool for Influenza Surveillance

The design and characterization of a low-density microarray for subtyping influenza A is presented. The microarray consisted of 15 distinct oligonucleotides designed to target only the matrix gene segment of influenza A. An artificial neural network was utilized to automate microarray image interpre...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2006-11, Vol.78 (22), p.7610-7615
Main Authors: Dawson, Erica D, Moore, Chad L, Smagala, James A, Dankbar, Daniela M, Mehlmann, Martin, Townsend, Michael B, Smith, Catherine B, Cox, Nancy J, Kuchta, Robert D, Rowlen, Kathy L
Format: Article
Language:English
Subjects:
Analytical chemistry
Arrays
Automation
Chemistry
Electrophoresis, Polyacrylamide Gel
Exact sciences and technology
Genes
Humans
Image Interpretation, Computer-Assisted - methods
Influenza
Influenza A virus - classification
Influenza A virus - genetics
Microscopy, Fluorescence
Molecular Diagnostic Techniques
Neural networks
Neural Networks (Computer)
Oligonucleotide Array Sequence Analysis - methods
Orthomyxoviridae - classification
Orthomyxoviridae - genetics
Reproducibility of Results
Sensitivity and Specificity
Spectrometric and optical methods
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Summary:The design and characterization of a low-density microarray for subtyping influenza A is presented. The microarray consisted of 15 distinct oligonucleotides designed to target only the matrix gene segment of influenza A. An artificial neural network was utilized to automate microarray image interpretation. The neural network was trained to recognize fluorescence image patterns for 68 known influenza viruses and subsequently used to identify 53 unknowns in a blind study that included 39 human patient samples and 14 negative control samples. The assay exhibited a clinical sensitivity of 95% and clinical specificity of 92%.
ISSN:0003-2700
1520-6882
DOI:10.1021/ac061739f