New syntax to describe local continuous structure-sequence information for recognizing new pre-miRNAs.
As an important complement to experimental identification of pre-miRNA, computational prediction methods are attracting more and more attention. Features extracted from pre-miRNA are the key to computational prediction. Among the features, local continuous structure-sequence information is usually employed by existing computational methods. As more and more species-specific miRNAs have been identified, a new syntax is required to describe pre-miRNA local continuous structure-sequence features. Therefore, we proposed here the use of couplet syntax to describe pre-miRNA intrinsic features. When tested on a dataset from miRBase12.0 with the use of features extracted by couplet syntax, the SVM classifier achieves a sensitivity of 81.98% and specificity of 87.16% on a human test set and a sensitivity of 86.71% on all other species. The obtained results indicate that the proposed couplet syntax can describe the intrinsic features of pre-miRNA better than traditional methods. By means of describing pre-miRNA secondary structure more precisely and masking frequently mutated nucleotides, couplet syntax provides a powerful feature-describing method that can be applied to many computational prediction methods.
Wang
Minghao
M
Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Song
Xiaofeng
X
Han
Ping
P
Li
Wei
W
Jiang
Bin
B
D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D035683:MicroRNAs / Q000737:chemistry / Q000145:classification / Q000235:genetics*; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D012322:RNA Precursors / Q000235:genetics*; D018749:RNA, Plant / Q000235:genetics; D012367:RNA, Viral / Q000235:genetics; D012984:Software; D013045:Species Specificity
D035683:MicroRNAs; D012322:RNA Precursors; D018749:RNA, Plant; D012367:RNA, Viral