Combined covariance model for non-coding RNA gene finding

Abstract

The use of covariance models in finding non-coding RNA gene members in genome sequence databases has been shown quite effective in many studies. However, it has a significant drawback, which is the very large computational burden. A combined covariance model is proposed to reduce the search complexity when a genome sequence is searched for more than one ncRNA gene family. The covariance models that are combined are selected using a hierarchical clustering algorithm. This study shows that when a small number of original covariance models are combined, the combined covariance model can find members from all original ncRNA families thus successfully reducing the search time.