Doctoral Thesis
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In the PhD-thesis a conditional random field approach and its implementation is presented to predict the interaction sites of protein homo- and heterodimers using the spatial structure of one protein partner from a complex. The method includes a substantially simple edge feature model. A novel node feature class is introduced that is called -change in free energy-. The Online Large-Margin algorithm is adapted in order to train the model parameters given a classified reference set of proteins. A significantly higher prediction accuracy is achieved by combining our new node feature class with the standard node feature class relative accessible surface area. The quality of the predictions is measured by computing the area under the receiver operating characteristic.