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

Fingerprint

Pathogens
Peptides
Antibody
Antibodies
Signal Processing
Signal processing
Processing
Random Maps
Epitopes
Process Variation
Random Sequence
Microarrays
Microarray
Waveform
Diagnostics
Determinant
Dependent

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

Biosequence time–frequency processing : Pathogen detection and identification. / O’Donnell, Brian; Maurer, Alexander; Papandreou-Suppappola, Antonia.

Applied and Numerical Harmonic Analysis. 9783319132297. ed. Springer International Publishing, 2015. p. 65-85 (Applied and Numerical Harmonic Analysis; No. 9783319132297).

Research output: Chapter in Book/Report/Conference proceedingChapter

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