Advanced Tree-Based Kernels for Protein Classification
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
Predicting palmitoylation sites using a regularised bio-basis function neural network
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Bayesian radial basis function neural network
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
Bio-kernel self-organizing map for HIV drug resistance classification
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Relevant and Non-Redundant Amino Acid Sequence Selection for Protein Functional Site Identification
International Journal of Software Science and Computational Intelligence
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A novel pattern recognition algorithm called an orthogonal kernel machine (OKM) is presented for the prediction of functional sites in proteins. Two novelties in OKM are that the kernel function is specially designed for measuring the similarity between a pair of protein sequences and the kernels are selected using the orthogonal method. Based on a set of well-recognized orthogonal kernels, this algorithm demonstrates its superior performance compared with other methods. An application of this algorithm to a real problem is presented.