Peak selection from MALDI-TOF mass spectra using ant colony optimization.
BACKGROUND
Due to the large number of peaks in mass spectra of low-molecular-weight (LMW) enriched sera, a systematic method is needed to select a parsimonious set of peaks to facilitate biomarker identification. We present computational methods for matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) spectral data preprocessing and peak selection. In particular, we propose a novel method that combines ant colony optimization (ACO) with support vector machines (SVM) to select a small set of useful peaks.


RESULTS
The proposed hybrid ACO-SVM algorithm selected a panel of eight peaks out of 228 candidate peaks from MALDI-TOF spectra of LMW enriched sera. An SVM classifier built with these peaks achieved 94% sensitivity and 100% specificity in distinguishing hepatocellular carcinoma from cirrhosis in a blind validation set of 69 samples. Area under the receiver operating characteristic (ROC) curve was 0.996. The classification capability of these peaks is compared with those selected by the SVM-recursive feature elimination method.


BACKGROUND
Supplementary material and MATLAB scripts to implement the methods described in this article are available at http://microarray.georgetown.edu/web/files/bioinf.htm.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Ressom
H W
HW
Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu
Varghese
R S
RS
Drake
S K
SK
Hortin
G L
GL
Abdel-Hamid
M
M
Loffredo
C A
CA
Goldman
R
R
D000465:Algorithms; D014408:Biomarkers, Tumor / Q000097:blood*; D006528:Carcinoma, Hepatocellular / Q000097:blood / Q000175:diagnosis; D019295:Computational Biology; D006801:Humans; D008103:Liver Cirrhosis / Q000097:blood; D008113:Liver Neoplasms / Q000097:blood / Q000175:diagnosis; D008954:Models, Biological; D008970:Molecular Weight; D010455:Peptides / Q000097:blood*; D040901:Proteomics; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
D014408:Biomarkers, Tumor; D010455:Peptides