title: Ovarian cancer identification based on dimensionality reduction for high-throughput mass spectrometry data.
abstract: BACKGROUND
  High-throughput and high-resolution mass spectrometry instruments are increasingly used for disease classification and therapeutic guidance. However, the analysis of immense amount of data poses considerable challenges. We have therefore developed a novel method for dimensionality reduction and tested on a published ovarian high-resolution SELDI-TOF dataset.
  
  
  RESULTS
  We have developed a four-step strategy for data preprocessing based on: (1) binning, (2) Kolmogorov-Smirnov test, (3) restriction of coefficient of variation and (4) wavelet analysis. Subsequently, support vector machines were used for classification. The developed method achieves an average sensitivity of 97.38% (sd = 0.0125) and an average specificity of 93.30% (sd = 0.0174) in 1000 independent k-fold cross-validations, where k = 2, ..., 10.
  
  
  BACKGROUND
  The software is available for academic and non-commercial institutions.
authors.affiliation: School of Electronics Engineering and Computer Science, Peking University, China.
authors.forename: J S
authors.initials: JS
authors.lastname: Yu
authors.forename: S
authors.initials: S
authors.lastname: Ongarello
authors.forename: R
authors.initials: R
authors.lastname: Fiedler
authors.forename: X W
authors.initials: XW
authors.lastname: Chen
authors.forename: G
authors.initials: G
authors.lastname: Toffolo
authors.forename: C
authors.initials: C
authors.lastname: Cobelli
authors.forename: Z
authors.initials: Z
authors.lastname: Trajanoski
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D014408:Biomarkers, Tumor / Q000032:analysis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D009363:Neoplasm Proteins / Q000032:analysis*; D010051:Ovarian Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000378:metabolism*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins