ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data
作者: Oluwatosin OluwadareJianlin Cheng
作者单位: 1University of Missouri
刊名: BMC Bioinformatics, 2017, Vol.18 (1)
来源数据库: Springer Journal
DOI: 10.1186/s12859-017-1931-2
关键词: ClusteringHi-CTopologically associated domain (TAD)CTCFChromosome conformation capturingGenome structureChromosome organization
英文摘要: With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function.
原始语种摘要: With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function.
全文获取路径: Springer  (合作)
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来源刊物:
影响因子:3.024 (2012)

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关键词翻译
关键词翻译
  • topologically 拓扑地
  • machine 机器
  • detecting 检测
  • computational 计算的
  • technique 技术
  • capturing 捕捉
  • conformation 构象
  • bounded 有界的
  • spatial 空间的
  • chromosomal 染色体的