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Research Article

Sensitive and Specific Peak Detection for SELDI-TOF Mass Spectrometry Using a Wavelet/Neural-Network Based Approach

  • Vincent A. Emanuele II mail,

    VEmanueleII@cdc.gov

    Affiliation: Chronic and Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

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  • Gitika Panicker,

    Affiliation: Chronic and Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

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  • Brian M. Gurbaxani,

    Affiliation: Chronic and Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

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  • Jin-Mann S. Lin,

    Affiliation: Chronic and Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

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  • Elizabeth R. Unger

    Affiliation: Chronic and Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

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  • Published: November 12, 2012
  • DOI: 10.1371/journal.pone.0048103

About the Authors

Vincent A. Emanuele II, Gitika Panicker, Brian M. Gurbaxani, Jin-Mann S. Lin, Elizabeth R. Unger
Chronic and Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

Corresponding Author

Email: VEmanueleII@cdc.gov

Competing Interests

Authors VAE and BMG have a pending patent application entitled, “Use of detector response curves to optimize settings for mass spectrometry,” application number PCT/US2011/055376 and depending from U.S. Provisional Application No. 61/390,910. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Author Contributions

Wrote the paper: VAE GP BMG. Conceived and designed computational experiments, performed computational experiments, analyzed the data with LibSELDI and manually validated peaks: VAE. Conceived and designed laboratory experiments: GP ERU. Performed laboratory experiments, analyzed the data with Ciphergen Express and manually validated peaks: GP. Provided biological interpretation of the data: BMG. Provided statistical interpretation of the clinical data: J-MSL. Revised manuscript critically for important intellectual content: J-MSL ERU.