A Non-coding RNA Sequence Alignment Algorithm Based on Improved Covariance Model

This paper attempts to overcome the inefficiency of covariance model (CM) in the search for non-coding sequence. For this purpose, the members of non-coding RNA family were compared and the CM of the family was discussed in details. Next, the CM was improved for structural units in the secondary structure, through the addition of the upper and lower limits on subsequence length. Based on the length distribution of each structural unit, the improved model limits the number of insertions and deletions during the evolution of sequences in the same family. After that, the author put forward a novel non-coding RNA sequence alignment algorithm. The experimental results show that the proposed algorithm can greatly reduce the computing time of non-coding RNA sequence comparison.