Feature extraction in the analysis of proteomic mass spectra.
Feature extraction or biomarker selection is a critical step in disease diagnosis and knowledge discovery based on protein MS. Many studies have discussed the classification methods applied in proteomics; however, few could be found to address feature extraction in detail. In this paper, we developed a systematic approach for the extraction of mass spectrum peak apex and peak area with special emphasis on noise filtration and peak calibration. Application to a head and neck cancer data generated at the Eastern Virginia Medical School [Wadsworth, J. T., Somers, K. D., Cazares, L. H., Malik, G. et al.., Clin. Cancer Res. 2004, 10, 1625-1632] revealed that the new feature extraction method would yield consistent and highly discriminatory biomarkers.
Wang
Xuena
X
State University of New York, Stony Brook, NY, USA.
Zhu
Wei
W
Pradhan
Kith
K
Ji
Chen
C
Ma
Yeming
Y
Semmes
Oliver John
OJ
Glimm
James
J
Mitchell
Joseph
J
D014408:Biomarkers, Tumor; D002138:Calibration; D019295:Computational Biology; D006258:Head and Neck Neoplasms / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods / Q000706:statistics & numerical data; D008956:Models, Chemical; D015233:Models, Statistical; D011506:Proteins / Q000032:analysis* / Q000737:chemistry; D040901:Proteomics / Q000379:methods*
D014408:Biomarkers, Tumor; D011506:Proteins