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Combined covariance model for non-coding RNA gene finding

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2 Author(s)
Wenbo Jiang ; Sch. of Comput. Sci., Simon Fraser Univ., Surrey, BC, Canada ; Wiese, K.C.

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.

Published in:

Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2011 IEEE Symposium on

Date of Conference:

11-15 April 2011

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