An analysis of disease-gene relationship from Medline abstracts by DigSee.

An analysis of disease-gene relationship from Medline abstracts by DigSee.
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DOI:
10.1038/srep40154
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发表时间:
2017-01-05
期刊:
影响因子:
4.6
通讯作者:
Lee H
Lee H
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Kim J;Kim JJ;Lee H

文献摘要

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疾病是由基因在生物事件中的异常行为引起的,例如基因调控、突变、磷酸化、表观遗传学和翻译后修饰。许多文本挖掘研究试图通过挖掘文献来确定基因与疾病之间的关系,但他们没有考虑基因响应疾病而表现出异常行为的生物事件。在这项研究中,我们建议通过 Medline 摘要中的生物事件来识别参与疾病发展的疾病相关基因。我们确定了 13,054 个基因与 4,494 种疾病类型之间的关联,这些基因比手动管理的所有疾病类型数据库(例如,在线人类孟德尔遗传)以及特定疾病(例如阿尔茨海默病和高血压)的数据库涵盖了更多的疾病相关基因。我们证明,根据 PubMed 量表,文本挖掘结果是可靠的,因为从文献范围内的发现推断出的疾病与疾病之间的关系与在一项著名研究中从手动管理的数据库中推断出的相似。此外,跨疾病类型的生物事件在文献范围内的分布揭示了疾病类型的不同特征。
Diseases are developed by abnormal behavior of genes in biological events such as gene regulation, mutation, phosphorylation, and epigenetics and post-translational modification. Many studies of text mining attempted to identify the relationship between gene and disease by mining the literature, but they did not consider the biological events in which genes show abnormal behaviour in response to diseases. In this study, we propose to identify disease-related genes that are involved in the development of disease through biological events from Medline abstracts. We identified associations between 13,054 genes and 4,494 disease types, which cover more disease-related genes than manually curated databases for all disease types (e.g., Online Mendelian Inheritance in Man) and also than those for specific diseases (e.g., Alzheimer’s disease and hypertension). We show that the text mining findings are reliable, as per the PubMed scale, in that the disease-disease relationships inferred from the literature-wide findings are similar to those inferred from manually curated databases in a well-known study. In addition, literature-wide distribution of biological events across disease types reveals different characteristics of disease types.
DOI: 10.1093/bioinformatics/btt156
发表时间: 2013-06-01
期刊: BIOINFORMATICS
影响因子: 5.8
作者:
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通讯作者: Lu, Zhiyong
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发表时间: 2008-02-01
期刊: TISSUE ANTIGENS
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DOI: 10.1093/nar/gkt531
发表时间: 2013-07
影响因子: 14.9
作者:
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使用中心性在文献挖掘的基因互动网络上识别基因 - 疾病的关联。
DOI: 10.1093/bioinformatics/btn182
发表时间: 2008-07-01
期刊: Bioinformatics (Oxford, England)
影响因子: --
作者:
Ozgür A;Vu T;Erkan G;Radev DR
通讯作者: Radev DR
DOI: 10.1093/database/bas061
发表时间: 2013
期刊: Database : the journal of biological databases and curation
影响因子: --
作者:
Dai HJ;Wu JC;Tsai RT;Pan WH;Hsu WL
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