Statistical Bioinformatics Webinar: Yu -- Gaussian Process Discriminant Analysis for Classification of Proteomics Mass Spectra

Biomarker detection and prognostic classification are common steps in the analysis of
proteomics mass spectrometry data.  However, many existing classifiers do not
incorporate the spectral nature of the data properly which may result in poor
classification performance.  In this talk, I will describe a newly developed Gaussian
process discriminant analysis that is suitable for classifying mass spectrometry data.
The proposed model incorporates feature selection and classification within a unified
framework.  The spectral nature of the data is accounted for with an appropriate
covariance function.  The computational efficiency of the model is kept within a
reasonable range through variational Bayes and computational shortcuts.  I will conclude
the talk with numerical results based on simulated and real datasets.