| Literature DB >> 16502467 |
Xuena Wang1, Wei Zhu, Kith Pradhan, Chen Ji, Yeming Ma, Oliver John Semmes, James Glimm, Joseph Mitchell.
Abstract
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.Entities:
Mesh:
Substances:
Year: 2006 PMID: 16502467 DOI: 10.1002/pmic.200500459
Source DB: PubMed Journal: Proteomics ISSN: 1615-9853 Impact factor: 3.984