Publication | Closed Access
A Discriminative Framework for Detecting Remote Protein Homologies
494
Citations
34
References
2000
Year
EngineeringStructural BioinformaticsMolecular BiologyNew Kernel FunctionGenomicsKernel FunctionGene RecognitionPattern RecognitionProteomicsRemote Protein HomologiesKnowledge DiscoveryProtein Structure PredictionDiscriminative FrameworkFunctional GenomicsBioinformaticsProtein BioinformaticsComputational BiologySystems BiologyMedicineKernel Method
A new method for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support vector machines using a new kernel function. The kernel function is derived from a generative statistical model for a protein family, in this case a hidden Markov model. This general approach of combining generative models like HMMs with discriminative methods such as support vector machines may have applications in other areas of biosequence analysis as well.
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