title: Identification of real microRNA precursors with a pseudo structure status composition approach.
abstract: Containing about 22 nucleotides, a micro RNA (abbreviated miRNA) is a small non-coding RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene expression. The human genome may encode over 1000 miRNAs. Albeit poorly characterized, miRNAs are widely deemed as important regulators of biological processes. Aberrant expression of miRNAs has been observed in many cancers and other disease states, indicating they are deeply implicated with these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Particularly, with the avalanche of RNA sequences generated in the postgenomic age, it is highly desired to develop computational sequence-based methods in this regard. Here two new predictors, called "iMcRNA-PseSSC" and "iMcRNA-ExPseSSC", were proposed for identifying the human pre-microRNAs by incorporating the global or long-range structure-order information using a way quite similar to the pseudo amino acid composition approach. Rigorous cross-validations on a much larger and more stringent newly constructed benchmark dataset showed that the two new predictors (accessible at http://bioinformatics.hitsz.edu.cn/iMcRNA/) outperformed or were highly comparable with the best existing predictors in this area.
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China; Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China; Gordon Life Science Institute, Belmont, Massachusetts, United States of America.
authors.forename: Bin
authors.initials: B
authors.lastname: Liu
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China.
authors.forename: Longyun
authors.initials: L
authors.lastname: Fang
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China.
authors.forename: Fule
authors.initials: F
authors.lastname: Liu
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China; Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China.
authors.forename: Xiaolong
authors.initials: X
authors.lastname: Wang
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China.
authors.forename: Junjie
authors.initials: J
authors.lastname: Chen
authors.affiliation: Gordon Life Science Institute, Belmont, Massachusetts, United States of America; Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia.
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000596:Amino Acids / Q000235:genetics; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods; D015894:Genome, Human / Q000235:genetics; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D009690:Nucleic Acid Conformation; D009711:Nucleotides / Q000235:genetics; D012322:RNA Precursors / Q000235:genetics*; D058727:RNA, Small Untranslated / Q000235:genetics
chemical_list: D000596:Amino Acids; D035683:MicroRNAs; D009711:Nucleotides; D012322:RNA Precursors; D058727:RNA, Small Untranslated
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