Using a VOMmodel for reconstructing potential coding regions in EST sequences

This paper presents a method for annotating coding and noncoding DNA regions by using variable order Markov (VOM) models. A main advantage in using VOMmodels is that their order may vary for different sequences, depending on the sequences’ statistics. As a result, VOMmodels are more flexible with respect to model parameterization and can be trained on relatively short sequences and on low-quality datasets, such as expressed sequence tags (ESTs). The paper presents a modified VOM model for detecting and correcting insertion and deletion sequencing errors that are commonly found in ESTs. In a series of experiments the proposedmethod is found to be robust to random errors in these sequences.