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.

Original languageEnglish (US)
Title of host publicationApplied and Numerical Harmonic Analysis
PublisherSpringer International Publishing
Pages65-85
Number of pages21
Edition9783319132297
DOIs
StatePublished - Jan 1 2015

Publication series

NameApplied and Numerical Harmonic Analysis
Number9783319132297
ISSN (Print)2296-5009
ISSN (Electronic)2296-5017

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Keywords

  • Detection
  • Epitope
  • Identification
  • Immunosignaturing
  • Pathogen
  • Random-sequence peptide microarray
  • Time–frequency processing

ASJC Scopus subject areas

  • Applied Mathematics

Cite this

O’Donnell, B., Maurer, A., & Papandreou-Suppappola, A. (2015). Biosequence time–frequency processing: Pathogen detection and identification. In Applied and Numerical Harmonic Analysis (9783319132297 ed., pp. 65-85). (Applied and Numerical Harmonic Analysis; No. 9783319132297). Springer International Publishing. https://doi.org/10.1007/978-3-319-13230-3_3