2010全国生物材料大会论文集之 (103).pdf

SusMiRPred: ab initio SVM classification for porcine
microRNA precursor prediction

De-Li Zhang §
Peng-Fang Zhou, Fei Zhang, Yang Zhang, Zhen-Hua Investigation Group of Molecular Virology, Immunology,
Zhao, Wen-Qian Zhang, Oncology & Systems Biology, Center for Bioinformatics,
Investigation Group of Molecular Virology, Immunology, and Research Laboratory of Virology, Immunology &
Oncology & Systems Biology, Center for Bioinformatics, Bioinformatics, College of Veterinary Medicine
and Research Laboratory of Virology, Immunology & Northwest A & F University
Bioinformatics, College of Veterinary Medicine Yangling, Shaanxi,
Northwest A & F University ******@.cn
Yangling, Shaanxi, §Corresponding author
zhoupengfang@


Abstract—MicroRNA (miRNA), which is short non-coding RNA, taxon specific [7]. Comparative approaches suffer lower
plays important roles in almost all biological processes examined. sensitivity in detecting novel pre-miRNAs without known
Several classifiers have been applied to predict humans, mice and homology pre-miRNAs [8]. But all of the porcine miRNA
rats precursor miRNAs (pre-miRNAs), but no classifier is sequences in the latest miRBase putationally
applied to classify porcine pre-miRNAs only based on the porcine predicted on the basis of sequence homology to known
pre-miRNAs because of litt