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机构地区:[1]军事医学科学院基础医学研究所计算生物学中心,北京100850
出 处:《微生物学报》2009年第1期1-5,共5页Acta Microbiologica Sinica
基 金:国家"863计划"(2006AA02Z323);国家自然科学基金(90608004;30470411)~~
摘 要:细菌sRNA是一类长度在40-500 nt之间的非编码RNA,主要以不完全碱基配对方式与靶标mRNA5′端相互作用进而发挥其生物学功能。鉴于预测方法可以为细菌sRNA及其靶标的实验发现提供指导,因此,细菌sRNA与靶标预测研究受到了广泛重视。文章首先将sRNA预测方法分为3类,分别是基于比较基因组学的预测方法、基于转录单元的预测方法和基于机器学习的预测方法;其次,将sRNA靶标预测方法分为2类,分别是序列比较方法与基于RNA二级结构的预测方法;最后对各类方法的原理、核心思想、优点和局限性进行了分析,并探讨了进一步的发展方向。Bacterial sRNAs are a class of non-coding RNAs with 40-500 nucleotides in length. Most of them function as posttranscriptional regulation of gene expression through binding to the translation initiation region of their target mRNAs. In view that prediction of sRNAs and their targets provides support for experimental identification, some prediction methods have been developed for both of them in recent years. In this review, we firstly gave an overview of methods for prediction of sRNA genes, which are classified into three categories, namely, comparative genomics-based, transcription units-based and machine learning- based prediction methods. Secondly, the methods for sRNA target prediction are classified into two types, which are sequence alignment-based method and prediction of RNA secondary structure-based method, respectively. Finally, the principles, advantages and limitations of each kind of method are discussed, and perspectives for prediction methods of sRNA and their targets is pointed out.
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