title: Novel approaches to smoothing and comparing SELDI TOF spectra.
abstract: BACKGROUND
  Most published literature using SELDI-TOF has used traditional techniques in Spectral Analysis such as Fourier transforms and wavelets for denoising. Most of these publications also compare spectra using their most prominent feature, i.e, peaks or local maximums.
  
  
  METHODS
  The maximum intensity value within each window of differentiable m/z values was used to represent the intensity level in that window. We also calculated the 'Area under the Curve' (AUC) spanned by each window.
  
  
  RESULTS
  Keeping everything else constant, such as pre-processing of the data and the classifier used, the AUC performed much better as a metric of comparison than the peaks in two out of three data sets. In the third data set both metrics performed equivalently.
  
  
  CONCLUSIONS
  This study shows that the feature used to compare spectra can have an impact on the results of a study attempting to identify biomarkers using SELDI TOF data.
authors.affiliation: Department of Medicine, Medical Statistics Section, University of Alabama at Birmingham,Birmingham, Alabama, USA. Sreelatha.Meleth@ccc.uab.edu
authors.forename: Sreelatha
authors.initials: S
authors.lastname: Meleth
authors.forename: Isam-Eldin
authors.initials: IE
authors.lastname: Eltoum
authors.forename: Liu
authors.initials: L
authors.lastname: Zhu
authors.forename: Denise
authors.initials: D
authors.lastname: Oelschlager
authors.forename: Chandrika
authors.initials: C
authors.lastname: Piyathilake
authors.forename: David
authors.initials: D
authors.lastname: Chhieng
authors.forename: William E
authors.initials: WE
authors.lastname: Grizzle