PMirP: A pre-microRNA prediction method based on structure-sequence hybrid features
PMirP: A pre-microRNA prediction method based on structure-sequence hybrid features
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PMirP：一种基于结构-序列混合特征的pre-microRNA预测方法
DOI：
10.1016/j.artmed.2010.03.004
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发表时间：
2010-06-01
影响因子：
7.5
通讯作者：
Liang, Yanchun
中科院分区：
文献类型：
--
作者：
Zhao, Dongyu;Wang, Yan;Liang, Yanchun
目的：MicroRNA是一类小分子非编码RNA，通常具有茎环结构。作为microRNA的重要阶段，前microRNA通过exportin 5从细胞核转运到细胞质，最后裂解为成熟microRNA。结构-序列特征和二级结构的最小自由能已被用于预测前体microRNA。方法：采用支持向量机对一种新的混合编码方案，结合自由核苷酸、二级结构自由能最小值和碱基配对特征，采用左三联体方法，对前体miRNA进行分类。人类前体microRNA数据集，其他11个物种和最新的前体microRNA序列用于test.Results：在这项研究中，我们开发了一种改进的方法，用于前体microRNA预测使用的各种功能和一个Web服务器称为PMirP的组合。预测真实的和假人前体microRNA的特异性和灵敏度分别高达98.4%和94.9%。公众可在www.example.com免费使用该网络服务器http://ccst.jlu.edu.cn/ci/bioinformatics/MiRNA（访问时间：结论：实验结果表明，与现有方法相比，该方法提高了预测效率和准确率。此外，PMirP具有较低的计算复杂度和较高的吞吐量预测能力比Mipred Web服务器。(C)2010 Elsevier B. V.保留所有权利。
Objective: MicroRNA is a type of small non-coding RNAs, which usually has a stem-loop structure. As an important stage of microRNA, the pre-microRNA is transported from nuclear to cytoplasm by exportin5 and finally cleaved into mature microRNA. Structure-sequence features and minimum of free energy of secondary structure have been used for predicting pre-microRNA. Meanwhile, the double helix structure with free nucleotides and base-pairing features is used to identify pre-miRNA for the first time.Methods: We applied support vector machine for a novel hybrid coding scheme using left-triplet method, the free nucleotides, the minimum of free energy of secondary structure and base-pairings features. Data sets of human pre-microRNA, other 11 species and the latest pre-microRNA sequences were used for testing.Results: In this study we developed an improved method for pre-microRNA prediction using a combination of various features and a web server called PMirP. The prediction specificity and sensitivity for real and pseudo human pre-microRNAs are as high as 98.4% and 94.9%, respectively. The web server is freely available to the public at http://ccst.jlu.edu.cn/ci/bioinformatics/MiRNA (accessed: 26 February 2010).Conclusions: Experimental results show that the proposed method improves the prediction efficiency and accuracy over existing methods. In addition, the PMirP has lower computational complexity and higher throughput prediction capacity than Mipred web server. (C) 2010 Elsevier B.V. All rights reserved.