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Nevertheless the stochastic step involved in the phylogeny-based method renders its predictions less reliable which is reflected by the weak predictive power of the method by itself.
The first type of preparing training set is more universal, but the second one better reflects the predictive power of the method.
The application to an independent validation dataset of alanine-mutations was used to show the predictive power of the method and yields a correlation coefficient of 0.51.
The reason for this choice is that many of attributes are nonlinear; thus, the predictive power of the method is increased.
The predictive power of the method was then tested using a blind test mutant database of 667 mutants, as well as a database of 82 protein protein complex mutants.
Cross-validation is performed on 13 known HIV receptors to evaluate the predictive power of the method.
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The predictive power of the methods is below that of SVM and PSSM which is not surprising as the prediction score based on sequence space is obtained by averaging over many sequence distances, an operation in which information on a single position in a sequence is lost.
However most importantly, the independent prognostic and predictive power of the methods can be compared using multi-variant analyses.
To compare the predictive power of the MCS method against the AP method and the hybrid approach, each method was coupled with SVMs to build a model for predicting bioactive compounds.
After training the Bayesian predictor and applying the bias correction we set out to assess the predictive power of this method for the interactions having at least two evidences.
In order to test the predictive power of this method and determine the optimal thresholds for solvent exposure and structure quality, a dataset of 1336 experimentally determined epitopes derived from 106 proteins was built (see methods section).
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