三维基因组数据分析方法进展
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清华大学自动化系,合成与系统生物学研究中心,生物信息学教育部重点实验室,北京信息科学与技术国家研究中心生物信息学研究部,清华大学自动化系,合成与系统生物学研究中心,生物信息学教育部重点实验室,北京信息科学与技术国家研究中心生物信息学研究部,清华大学自动化系,合成与系统生物学研究中心,生物信息学教育部重点实验室,北京信息科学与技术国家研究中心生物信息学研究部

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国家自然科学基金(31371341, 61773230, 61721003)和清华大学自主科研项目(20141081175)资助


The Advancement of Analysis Methods of Chromosome Conformation Capture Data
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Department of Automation, Center for Synthetic and Systems Biology, Tsinghua University; Ministry of Education Key Laboratory of Bioinformatics; Bioinformatics Division, BNRIST,Department of Automation, Center for Synthetic and Systems Biology, Tsinghua University; Ministry of Education Key Laboratory of Bioinformatics; Bioinformatics Division, BNRIST,Department of Automation, Center for Synthetic and Systems Biology, Tsinghua University; Ministry of Education Key Laboratory of Bioinformatics; Bioinformatics Division, BNRIST

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This work was supported by grants from The National Natural Science Foundation of China (31371341, 61773230, 61721003) and Tsinghua University Initiative Scientific Research Program (20141081175)

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    摘要:

    对染色质三维结构的探究逐渐成为了解基因组功能与基因调控关系的必要手段.近年来,随着高通量染色体构象捕获(Hi-C)等技术的发展和高通量测序成本的降低,全基因组交互作用的数据量快速增长,交互作用图谱分辨率不断提高.这给三维基因组学发展带来机遇的同时,也给计算建模带来了挑战.当前,三维基因组数据的分析方法覆盖面广,包括了数据前期处理、标准化、可视化、特征提取、三维建模等环节,但是如何从中选择高效、准确的方法却成为制约研究者们开展研究的一项关键因素.本文根据这些方法的适用场景、原理及特点进行系统地归纳,并重点关注了针对新技术或新需求的分析方法,以期促进这一领域中信息学方法的应用和开发,助力三维基因组学的研究.

    Abstract:

    The investigation about chromatin 3D structure is becoming one indispensable way in studying genome functions and gene regulation. In past several years, thanks to the development of chromatin conformation capture technology and decreasing cost of high throughput sequencing, the amount of whole-genome interaction data increases rapidly with the ascending resolutions. This not only brought the chances for interpreting 3D genome, but also challenged the modeling methods. Nowadays, methods of analyzing these data covered a wide range, including pre-processing, normalization, visualization, features extraction and 3D modeling; however, choosing efficient and precise computational methods becomes an obstacle limiting the study of 3D genome. In this paper, we sum up these methods according to their suitable conditions, principles and characters and focus on the methods for new technologies and requirements in order to promote the application and development of these methods, assisting the investigation of 3D genome.

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张祥林,方欢,汪小我.三维基因组数据分析方法进展[J].生物化学与生物物理进展,2018,45(11):1093-1105

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历史
  • 收稿日期:2018-04-04
  • 最后修改日期:2018-06-21
  • 接受日期:2018-06-22
  • 在线发布日期: 2018-06-22
  • 出版日期: 2018-11-20
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