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kernel methods in bioinformatics
course outline
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A biological introduction
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Kernels: using linear machinery to solve nonlinear problems
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Large margin classifiers: support vector machines
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SVM tricks of the trade
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Kernels for biological data
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String kernels: inexact string matching kernels, local alignment kernels, all-subsequences kernel
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Kernels for graphs and networks: classifying protein structures, predicting protein function
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Kernels from generative models (Fisher kernels)
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Data fusion with kernel methods
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Multi-class classification
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Feature selection for kernel methods: classifying gene expression data
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Kernel methods for structured outputs
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Proper design of machine learning experiments in bioinformatics
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