13. A system for classifying sequences comprising: a parameter estimator configured to receive a first training set representing first sequences having a first classification and a second training set representing second sequences, different than the first sequences, having a second classification, and to establish Markov Model parameters for the first classification based on the first and the second training sets; and a classifier configured to receive a classification set representing third sequences having an unknown classification and to classify the third sequences based upon the established Markov Model parameters.
13. A system for classifying sequences comprising: a parameter estimator configured to receive a first training set representing first sequences having a first classification and a second training set representing second sequences, different than the first sequences, having a second classification, and to establish Markov Model parameters for the first classification based on the first and the second training sets; and a classifier configured to receive a classification set representing third sequences having an unknown classification and to classify the third sequences based upon the established Markov Model parameters. 14. A system according to claim 13, wherein: the parameter estimator is further configured to generate first Markov Model coefficients associated with the first training set and second Markov Model coefficients associated with the second training set, to adjust the generated first coefficients to be maximally dissimilar to the second coefficients, and to establish the Markov Model parameters based on the adjusted first coefficients.