Details

Autor(en) / Beteiligte

• Lin Zhang
• Jian-Qiu Zhang
• Xiao-Bo Zhou
• Hong-Hui Wang
• Yu-Fei Huang
• Hui Liu
• Wong, S.

Titel

Feature selection and classification of prO-TOF data based on soft information

Ist Teil von

• 2008 International Conference on Machine Learning and Cybernetics, 2008, Vol.7, p.4018-4023

Ort / Verlag

IEEE

Erscheinungsjahr

2008

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• In this paper, we introduce a feature selection and classification method for prOTOF Mass Spectrometry (MS) data profiles of diseased and healthy patients. The method is based on a special statistical measure, which quantifies the probability of the existence of peptidepeaks. A special ranking score that is based on the statistical measure is used for selecting features that can best distinguish diseased and healthy data profiles. Based on the selected features, we applied a variety of classification algorithms and the results are compared with that of a method which selects features only based on peak heights. The results show a significant improvement in classification error rate with our proposed method.