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By Timothy Meekhof and Robert B. Heckendorn


We describe a Markov chain Bayesian classification tool, SCS, that can perform data-driven classification of proteins and protein segments. Training data for interesting classification problems is often limited; thus, SCS uses string transformation functions to change the encoding of proteins to reduce problem perplexity and improve classification. A wrapperbased genetic algorithm is used to search the space of possible string transformation functions to find functions that improve classification

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Year: 2009
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