@inbook{7d035a0e99cd4d508f3b91240949cd0f,
title = "Biosequence time–frequency processing: Pathogen detection and identification",
abstract = "Diagnostic information obtained from antibodies binding to random peptide sequences is now feasible using immunosignaturing, a recently developed microarray technology. The success of this technology is highly dependent upon the use of advanced algorithms to analyze the random sequence peptide arrays and to process variations in antibody profiles to discriminate between pathogens. This work presents the use of time–frequency signal processing methods for immunosignaturing. In particular, highly-localized waveforms and their parameters are used to uniquely map random peptide sequences and their properties in the time–frequency plane. Advanced time–frequency signal processing techniques are then applied for estimating antigenic determinants or epitope candidates for detecting and identifying potential pathogens.",
keywords = "Detection, Epitope, Identification, Immunosignaturing, Pathogen, Random-sequence peptide microarray, Time–frequency processing",
author = "Brian O{\textquoteright}Donnell and Alexander Maurer and Antonia Papandreou-Suppappola",
note = "Funding Information: The authors gratefully acknowledge Dr. Stephen A. Johnston, Dr. Phillip Stafford and Joshua Richer (Director, Associate Professor Research, and Graduate Research Assistant, respectively, of the Center for Innovations in Medicine, Biodesign Institute, Arizona State University) for providing the immunosignaturing data used in this work and for valuable discussions on the epitope estimation algorithm. This work was supported by the Defense Threat Agency Reduction Contract HDTRA1-12-C-0058. Funding Information: Acknowledgements The authors gratefully acknowledge Dr. Stephen A. Johnston, Dr. Phillip Stafford and Joshua Richer (Director, Associate Professor Research, and Graduate Research Assistant, respectively, of the Center for Innovations in Medicine, Biodesign Institute, Arizona State University) for providing the immuno-signaturing data used in this work and for valuable discussions on the epitope estimation algorithm. This work was supported by the Defense Threat Agency Reduction Contract HDTRA1-12-C-0058. Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.",
year = "2015",
doi = "10.1007/978-3-319-13230-3_3",
language = "English (US)",
series = "Applied and Numerical Harmonic Analysis",
publisher = "Springer International Publishing",
number = "9783319132297",
pages = "65--85",
booktitle = "Applied and Numerical Harmonic Analysis",
edition = "9783319132297",
}