SSCA, an algorithm for selecting sequences to use in RNA secondary structure prediction by the comparative approach
Résumé
One way to predict the secondary structure of an RNA is to use the comparative approach, which consists of identifying mutations and identitties from homologous sequence alignments. The sequences must covary enough for compensatory mutations to be revealed, but comparison is difficult if they are too different. Thus the choice of homologous sequences is critical. While many possible combinations of homologous sequences may be used for prediction, only a few will give good structure predictions. We have developed an algorithm, SSCA, which measures the suitability of sequences for the comparative approach. It is based on evolutionary models with structure constraints, particularly those on sequence variations and stem alignment.