title: Identification of microRNAs and natural antisense transcript-originated endogenous siRNAs from small-RNA deep sequencing data.
abstract: Next-generation sequencing (NGS) is becoming a routine experimental technology. It has been a great success in recent years to profile small-RNA species using NGS. Indeed, a large quantity of small-RNA profiling data has been generated from NGS, and computational methods have been developed to process and analyze NGS data for the purpose of identification of novel and expressed small noncoding RNAs and analysis of their roles in nearly all biological processes and pathways in eukaryotes. We discuss here the computational procedures and major steps for identification of microRNAs and natural antisense transcript-originated small interfering RNAs from NGS small-RNA profiling data.
authors.affiliation: Department of Computer Science and Engineering, Fudan University, Shanghai, China. weixiong.zhang@wustl.edu
authors.forename: Weixiong
authors.initials: W
authors.lastname: Zhang
authors.forename: Xuefeng
authors.initials: X
authors.lastname: Zhou
authors.forename: Jing
authors.initials: J
authors.lastname: Xia
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhou
mesh_terms: D020451:Contig Mapping / Q000379:methods; D020869:Gene Expression Profiling; D056426:Genetic Loci; D059014:High-Throughput Nucleotide Sequencing; D035683:MicroRNAs / Q000235:genetics*; D034741:RNA, Small Interfering / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software
chemical_list: D035683:MicroRNAs; D034741:RNA, Small Interfering