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Time-Frequency Analysis of Peptide Microarray Data: Application to Brain Cancer Immunosignatures

Abstract One of the gravest dangers facing cancer patients is an extended symptom-free lull between tumor initiation and the first diagnosis. Detection of tumors is critical for effective intervention. Using the body’s immune system to detect and amplify tumor-specific signals may enable detection of cancer using an inexpensive immunoassay. Immunosignatures are one such assay: they provide a map of antibody interactions with random-sequence peptides. They enable detection of disease-specific patterns using classic train/test methods. However, to date, very little effort has gone into extracting information from the sequence of peptides that interact with disease-specific antibodies. Because it is difficult to represent all possible antigen peptides ... (more)
Created Date 2015-06-18
Contributor O'Donnell, Brian (ASU author) / Maurer, Alexander (ASU author) / Papandreou-Suppappola, Antonia (ASU author) / Stafford, Phillip (ASU author) / Ira A. Fulton Schools of Engineering / School of Electrical, Computer and Energy Engineering / Biodesign Institute / Innovations in Medicine
Type Text
Extent 15 pages
Language English
Identifier DOI: 10.4137/CIN.S17285 / ISSN: 1176-9351
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Citation O'Donnell, B., Maurer, A., Papandreou-Suppappola, A., & Stafford, P. (2015). Time-Frequency Analysis of Peptide Microarray Data: Application to Brain Cancer Immunosignatures. Cancer Informatics, 219. doi:10.4137/cin.s17285
Note The final version of this article, as published in Cancer Informatics, can be viewed online at:
Collaborating Institutions ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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