A One-Class Classification Approach for Protein Sequences and Structures

Abstract. The One-Class Classification (OCC) approach is based on the assumption that samples are available only from a target class in the train-ing phase.OCCmethods have been applied with success to problemswhere the classes are very different in size. As class-imbalance problems are typi-cal in protein classification tasks, we were interested in testing one-class classification algorithms for the detection of distant similarities in pro-tein sequences and structures. We found that the OCC approach brought about a small improvement in classification performance compared to bi-nary classifiers (SVM, ANN, Random Forest). More importantly, there is a substantial (50 to 100 fold) improvement in the training time. OCCs may provide an especially useful alternative for processing those protein groups where discriminative classifiers cannot be easily trained