ComputingBioinformaticsComputer ScienceData MiningFeature EngineeringMachine LearningInformation ExtractionRna SplicingSupport Vector MachinesBinary EncodingBinary Vector SystemsData EncodingFeature EncodingSplice Site PredictionSplicing Detection
In splice sites prediction, the information contained in false splice sites is often ignored, which has been recognized to be very valuable. In this paper, three novel encoding approaches, MCM with DTF, MCM with UTF and WAM with UTF, are described, all of which consider the information both in true and false splice sites. From the comparison with 5 other encoding methods, we can conclude: (1) SVM can benefit from the information contained in false splice sites as well as in true splice sites. ( (3) The performance of binary vector encoding method is surprisingly good, the potential of which need to be further investigated.
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