String transformation-based Bayesian classification or proteins

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 wrapper-based genetic algorithm is used to search the space of possible string transformation functions to find functions that improve classification.