The protein spectrometry holds such characteristics of complex and large volumes of data that the general statistical methods can't satisfy the demand of disease prediction or classification. Several kinds of main methods of mass spectrometry data mining,such as decision tree analysis, partial least squares, artificial neural networks and support vector machines is overviewed in bioinformatics perspective. And examples of different methods used to diagnose disease are illustrated. These show an important role of mass spectrometry in identification and prediction of disease.
Artificial Intelligence ; Computational Biology ; Data Mining ; Decision Trees ; Least-Squares Analysis ; Mass Spectrometry ; Neural Networks (Computer) ; Support Vector Machine