首页 | 本学科首页   官方微博 | 高级检索  
   检索      

基于表观基因组学的DNA元件鉴定方法研究进展
引用本文:卢一鸣,屈武斌,张成岗.基于表观基因组学的DNA元件鉴定方法研究进展[J].生物化学与生物物理进展,2014,41(7):640-648.
作者姓名:卢一鸣  屈武斌  张成岗
作者单位:军事医学科学院放射与辐射医学研究所,蛋白质组学国家重点实验室,北京 100850,军事医学科学院放射与辐射医学研究所,蛋白质组学国家重点实验室,北京 100850,军事医学科学院放射与辐射医学研究所,蛋白质组学国家重点实验室,北京 100850
基金项目:国家重点基础研究发展计划(973)(2012CB518200),国家自然科学基金(30900862, 30973107, 81070741, 81172770),蛋白质组学国家重点实验室自主研究及开放课题(SKLP-O201104,SKLP-K201004,SKLP-O201002)和国家科技重大专项(2012ZX09102301-016)资助项目
摘    要:在人类基因组测序已经完成的"后基因组"时代,对基因组序列的功能注释,尤其是各种DNA调控元件的鉴定,已成为进一步理解人类基因组复杂机制的瓶颈问题.最近,针对染色质状态图谱的大规模研究工作,揭示了各类DNA元件特征性的染色质修饰标记.这些研究结果推动了一系列基于有监督和无监督学习的DNA元件预测方法的产生,其中一些方法已经成功应用于多个基因组的DNA元件预测,并且已成为未知基因组的常规注释工具.这些预测方法因其算法特点和预测策略不同而适用于不同类型的DNA元件预测任务.大多数情况下,使用者需要联合使用多个预测方法来达到预测敏感性和特异性的平衡.尽管各类算法在DNA元件预测中都有一些成功的应用,但每一类算法都有其特有的弊端,需要使用者认真避免.本文回顾了前期和当下DNA元件预测方法的主要类型,全面分析了各类方法的优缺点,指出了下一步可以改进的方向.本综述中的分析和观点有助于读者深入理解DNA元件预测算法的主要原则,进而在相关研究中更好地应用这些方法.

关 键 词:DNA元件  基因表达调控  表观基因组学  机器学习
收稿时间:6/7/2013 12:00:00 AM
修稿时间:2013/12/17 0:00:00

Methods of DNA Elements Identification in Epigenomics
LU Yi-Ming,QU Wu-Bin and ZHANG Cheng-Gang.Methods of DNA Elements Identification in Epigenomics[J].Progress In Biochemistry and Biophysics,2014,41(7):640-648.
Authors:LU Yi-Ming  QU Wu-Bin and ZHANG Cheng-Gang
Institution:Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, China,Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, China and Beijing Institute of Radiation Medicine, State Key Laboratory of Proteomics, Beijing 100850, China
Abstract:In the post-genomic era after human whole-genome sequencing has been completed, accurate functional annotation of genomic sequences, especially the DNA regulatory elements, has become an urgent need of further in-depth understanding of the complex mechanisms of human genome. Recent large-scale chromatin states mapping efforts have revealed characteristic chromatin modification signatures for various types of functional DNA elements. The conclusions drew in these studies have promoted the emergence of a series of supervised and unsupervised methods of DNA elements identification, some of which have been successfully applied to identify functional DNA elements in a number of genomes and have become the regular tools to decode an unknown genome. These methods are adept at different aspects of genomic studies, varied by the embedded algorithms and the identification strategies. In most cases users should consider joint application of different types of methods to obtain a balance between identification sensitivity and specificity. Despite the successful applications of current methods, each type of methods has its own disadvantages which users should scrupulously avoid. In this paper, we not only reviewed the main types of previous and current DNA elements identification methods, and comprehensively analyzed the advantages and disadvantages of each type of methods, but also pointed out the next possible directions of method improvement. We anticipated the analysis and views put forward in this review could help readers to deepen the understanding of principles of DNA elements identification methods, thus better applied them in their own studies.
Keywords:DNA elements  regulation of gene expression  epigenomics  machine learning
本文献已被 CNKI 等数据库收录!
点击此处可从《生物化学与生物物理进展》浏览原始摘要信息
点击此处可从《生物化学与生物物理进展》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号