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Predictive Modeling in Proteomics-based Disease Detection
James Cook Univ., Townsville .ORCID iD: 0000-0002-4255-5130
2007 (English)Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

Recent advent of mass-spectrometry data generated by proteomic technology provides a new type of biological information which is very promising in the search for diagnostic and therapeutic approaches that enables the early detection of fatal diseases and the development of personalized medicine. Successful analysis of such high-throughput proteomic data relies much on signal-processing and pattern-recognition techniques. This paper addresses the application of prediction models for cancer detection using mass spectral data.

Place, publisher, year, edition, pages
2007. 3308-3311 p.
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-125026DOI: 10.1109/iembs.2007.4353037ISBN: 978-1-4244-0787-3 (print)OAI: oai:DiVA.org:liu-125026DiVA: diva2:902765
Conference
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. 22-26 Aug. 2007 Lyon
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2016-02-23

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Pham, Tuan D
Bioinformatics (Computational Biology)

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
  • vancouver
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Language
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Output format
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