A Non-deterministic Grammar Inference Algorithm Applied to the Cleavage Site Prediction Problem in Bioinformatics

We report results on applying the OIL (Order Independent Language) grammar inference algorithm to predict cleavage sites in polyproteins from translation of Potivirus genome. This non-deterministic algorithm is used to generate a group of models which vote to predict the occurrence of the pattern. We built nine models, one for each cleavage site in this kind of virus genome and report sensibility, specificity, accuracy for each model. Our results show that this technique is useful to predict cleavage sites in the given task with accuracy rates higher than 95%.