Gaussian Process: A Promising Approach for the Modeling and Prediction of Peptide Binding Affinity to MHC Proteins

Abstract excerpt

On the basis of Bayesian probabilistic inference, Gaussian process (GP) is a powerful machine learning method for nonlinear classification and regression, but has only very limited applications in the new areas of computational vaccinology and immunoinformatics. In the current work, we present a paradigmatic study of using GP regression technique to quantitatively model and predict the binding affinities of over...

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