Training finite state machines to improve PCR primer design

We present preliminary results on training finite state machines (FSMs) as good/bad classifiers for polymerase chain reaction (PCR) primers. Novel features of the work presented include hybridization of multiple populations of FSMs and an incremental fitness function. The system presented here is a post-production add-on to a standard primer picking program intended to compensate for organism and lab specific factors.