Use of linear regression model to compare RNA secondary structures

With more and more ribonucleic acid (RNA) secondary structures accumulated, the need for comparing different RNA secondary structures often arises in function prediction and evolutionary analysis. Numerous efficient algorithms were developed for comparing different RNA secondary structures, but challenges remain. In this paper, six new models based on the linear regression model were proposed for the comparison of RNA secondary structures. The proposed models were tested on a mixed data, containing six secondary structures from RNase P RNAs, three secondary structures from SSU rRNA and five secondary structures from 16S ribosomal RNAs. The results have shown the effectiveness of the proposed models. Moreover, the time complexity of our models is favorable by comparing with that of the existing methods which solve the similar problem.