A literature network of human genes for high-throughput analysis of gene expression
A literature network of human genes for high-throughput analysis of gene expression
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DOI：
10.1038/ng0501-21
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发表时间：
2001-05-01
期刊：
影响因子：
30.8
通讯作者：
Hovig, E
中科院分区：
文献类型：
--
作者：
Jenssen, TK;Lægreid, A;Hovig, E
我们已经从公共可用的基因和文本数据库中自动提取了显式和隐式生物医学知识，以通过超过1000万Medline记录中的标题和摘要来创建13,712个名为人类基因的基因与基因共同引用网络。基因之间的关联已通过将基因与医学主题标题（网格）指数和基因本体学（CO）数据库的术语联系起来的术语进行注释。用于基因表达分析的提取的数据库和随附的Web工具统称为“ Pubgene”。我们通过三个大规模实验验证了提取的网络，表明共同发生反映了生物学上有意义的关系，从而提供了一种提取和结构已知生物学的方法。我们通过分析两个公开可用的微阵列数据集来验证工具的适用性。
We have carried out automated extraction of explicit and implicit biomedical knowledge from publicly available gene and text databases to create a gene-to-gene co-citation network for 13,712 named human genes by automated analysis of titles and abstracts in over 10 million MEDLINE records. The associations between genes have been annotated by linking genes to terms from the medical subject heading (MeSH) index and terms from the gene ontology (CO) database. The extracted database and accompanying web tools for gene-expression analysis have collectively been named 'PubGene'. We validated the extracted networks by three large-scale experiments showing that co-occurrence reflects biologically meaningful relationships, thus providing an approach to extract and structure known biology. We validated the applicability of the tools by analyzing two publicly available microarray data sets.