title: Analysis of mass spectral serum profiles for biomarker selection.
abstract: BACKGROUND
  Mass spectrometric profiles of peptides and proteins obtained by current technologies are characterized by complex spectra, high dimensionality and substantial noise. These characteristics generate challenges in the discovery of proteins and protein-profiles that distinguish disease states, e.g. cancer patients from healthy individuals. We present low-level methods for the processing of mass spectral data and a machine learning method that combines support vector machines, with particle swarm optimization for biomarker selection.
  
  
  RESULTS
  The proposed method identified mass points that achieved high prediction accuracy in distinguishing liver cancer patients from healthy individuals in SELDI-QqTOF profiles of serum.
  
  
  BACKGROUND
  MATLAB scripts to implement the methods described in this paper are available from the HWR's lab website http://lombardi.georgetown.edu/labpage
authors.affiliation: Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA. hwr@georgetown.edu
authors.forename: Habtom W
authors.initials: HW
authors.lastname: Ressom
authors.forename: Rency S
authors.initials: RS
authors.lastname: Varghese
authors.forename: Mohamed
authors.initials: M
authors.lastname: Abdel-Hamid
authors.forename: Sohair Abdel-Latif
authors.initials: SA
authors.lastname: Eissa
authors.forename: Daniel
authors.initials: D
authors.lastname: Saha
authors.forename: Lenka
authors.initials: L
authors.lastname: Goldman
authors.forename: Emanuel F
authors.initials: EF
authors.lastname: Petricoin
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Conrads
authors.forename: Timothy D
authors.initials: TD
authors.lastname: Veenstra
authors.forename: Christopher A
authors.initials: CA
authors.lastname: Loffredo
authors.forename: Radoslav
authors.initials: R
authors.lastname: Goldman
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D014408:Biomarkers, Tumor / Q000097:blood*; D001774:Blood Chemical Analysis / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D008113:Liver Neoplasms / Q000097:blood* / Q000175:diagnosis*; D009363:Neoplasm Proteins / Q000097:blood*; D010449:Peptide Mapping / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins