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Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology

机译:用基因本体和病理学注释人类基因组的功能

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Increasing evidences indicated that function annotation of human genome in molecular level and phenotype level is very important for systematic analysis of genes. In this study, we presented a framework named Gene2Function to annotate Gene Reference into Functions (GeneRIFs), in which each functional description of GeneRIFs could be annotated by a text mining tool Open Biomedical Annotator (OBA), and each Entrez gene could be mapped to Human Genome Organisation Gene Nomenclature Committee (HGNC) gene symbol. After annotating all the records about human genes of GeneRIFs, 288,869 associations between 13,148 mRNAs and 7,182 terms, 9,496 associations between 948 microRNAs and 533 terms, and 901 associations between 139 long noncoding RNAs (IncRNAs) and 297 terms were obtained as a comprehensive annotation resource of human genome. High consistency of term frequency of individual gene (Pearson correlation = 0.6401, p = 2.2e - 16) and gene frequency of individual term (Pearson correlation = 0.1298, p = 3.686e - 14) in GeneRIFs and GOA shows our annotation resource is very reliable.
机译:增加证据表明,在分子水平和表型水平中,人类基因组的功能注释对于基因的系统分析非常重要。在这项研究中,我们介绍了一个名为Gene2Function的框架,以将基因参考注释为功能(Generifs),其中Generifs的每个功能描述可以通过文本挖掘工具开放生物医学注释(OBA)来注释,并且每个Entrez基因都可以映射到人类基因组组织基因命名委员会(HGNC)基因符号。在注释关于人类基因的所有记录之后,在13,148 mRNA和7,182术语之间的288,869个关联,948 microRNA和533个术语之间的9,496个关联,并且获得了901个关联,在139年之间的关联中,获得了综合注释资源人类基因组。单个基因术语频率的高一致性(Pearson相关= 0.6401,p = 2.2e -16)和个人术语的基因频率(Pearson相关= 0.1298,p = 3.686e -14)在Generifs和Goa中显示了我们的注释资源非常可靠的。

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