上海大学学报(自然科学版) ›› 2010, Vol. 16 ›› Issue (1): 75-80.

• 数理化科学 • 上一篇    下一篇

MiRfilter:一个预测病毒microRNA的计算工具

张玉滨,赵洁苑,龚云路,王翼飞   

  1. (上海大学 理学院,上海 200444)
  • 收稿日期:2008-04-28 出版日期:2010-02-28 发布日期:2010-02-28
  • 通讯作者: 王翼飞(1948~),男,教授,博士生导师,研究方向为计算分子生物学. E-mail:yifei_wang@staff.shu.edu.cn
  • 基金资助:

    国家高技术研究发展计划(863计划)资助项目(2002AA02Z190 )

A Computational Method for Prediction and Detection of microRNAs

ZHANG Yu-bin,ZHAO Jie-yuan,GONG Yun-lu,WANG Yi-fei   

  1. (College of Sciences, Shanghai University, Shanghai 200444, China)
  • Received:2008-04-28 Online:2010-02-28 Published:2010-02-28

摘要:

采用生物信息学方法开发了一个预测病毒miRNA的计算机程序MiRfilter,通过提取已知的病毒miRNA的生物学特征,规定参数及参数范围,并以此为筛选标准,预测潜在的病毒miRNA.用EBV和RLCV两种病毒的正负样本对MiRfilter的预测精度进行检测.MiRfilter从39个EBV已知的miRNA中正确识别了30个,从116个负数据中检测到9个假阳性数据;从20个RLCV的miRNA中正确识别了15个,从108个负数据中检测到2个假阳性数据.用取自果蝇和线虫预测区域的186个负数据检测MiRfilter的特异性,在186个负数据中没有预测出假阳性序列.

关键词: 病毒miRNA;MiRfilter;生物基因组;发夹结构;生物学特征

Abstract:

 This paper develops a computational procedure named MiRfilter to predict the virus miRNAs. MiRfilter selects some important biological features of miRNAs as parameters to predict the potential precursors and miRNAs. When using two samples to test MiRfilter’s accuracy, it successfully retrieves 30 EBVencoded miRNAs from 39 known ones, and predicts 9 false positive miRNAs from 116 negative ones. Then it retrieves 15 RLCV-encoded miRNAs from 20 known ones and predicts 2 false miRNAs from 108 negative ones. Further, when using another species to test MiRfilter’s specificity, it predicts none false positive miRNA from 186 negative ones in D.melanogaster and C.elegans. 

Key words:  virus miRNA; MiRfilter; biology genome; hairpin structure; biological features

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