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Using the literature-based discovery paradigm to investigate drug mechanisms.运用基于文献的发现范式来研究药物作用机制。
AMIA Annu Symp Proc. 2007 Oct 11;2007:6-10.
2
Extracting semantic predications from Medline citations for pharmacogenomics.从医学文献数据库(Medline)引用中提取药物基因组学的语义谓词。
Pac Symp Biocomput. 2007:209-20.
3
Semantic MEDLINE for discovery browsing: using semantic predications and the literature-based discovery paradigm to elucidate a mechanism for the obesity paradox.用于发现式浏览的语义医学文献数据库:利用语义断言和基于文献的发现范式阐明肥胖悖论的机制
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Graph-based methods for discovery browsing with semantic predications.基于语义谓词的图方法用于发现式浏览。
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Pharmacogenet Genomics. 2007 Nov;17(11):989-93. doi: 10.1097/FPC.0b013e3282f01aa3.

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本文引用的文献

1
Exploiting semantic relations for literature-based discovery.利用语义关系进行基于文献的发现。
AMIA Annu Symp Proc. 2006;2006:349-53.
2
Risk for cancer in a cohort of patients hospitalized for schizophrenia in Denmark, 1969-1993.1969 - 1993年丹麦因精神分裂症住院的一组患者的癌症风险
Schizophr Res. 2005 Jun 15;75(2-3):315-24. doi: 10.1016/j.schres.2004.11.009. Epub 2004 Dec 13.
3
Using literature-based discovery to identify disease candidate genes.利用基于文献的发现来识别疾病候选基因。
Int J Med Inform. 2005 Mar;74(2-4):289-98. doi: 10.1016/j.ijmedinf.2004.04.024.
4
A knowledgebase system to enhance scientific discovery: Telemakus.一个用于促进科学发现的知识库系统:忒勒马科斯。
Biomed Digit Libr. 2004 Sep 21;1:2. doi: 10.1186/1742-5581-1-2. eCollection 2004.
5
Mining MEDLINE for implicit links between dietary substances and diseases.从医学在线数据库(MEDLINE)中挖掘饮食物质与疾病之间的潜在联系。
Bioinformatics. 2004 Aug 4;20 Suppl 1:i290-6. doi: 10.1093/bioinformatics/bth914.
6
The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text.自然语言处理中领域知识与语言结构的相互作用:解读生物医学文本中的上位命题
J Biomed Inform. 2003 Dec;36(6):462-77. doi: 10.1016/j.jbi.2003.11.003.
7
Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program.生物医学文本到UMLS元词表的有效映射:MetaMap程序
Proc AMIA Symp. 2001:17-21.
8
Supporting discovery in medicine by association rule mining in Medline and UMLS.通过在医学文献数据库(Medline)和一体化医学语言系统(UMLS)中进行关联规则挖掘来支持医学发现。
Stud Health Technol Inform. 2001;84(Pt 2):1344-8.
9
Text-based discovery in biomedicine: the architecture of the DAD-system.生物医药领域基于文本的发现:DAD系统的架构
Proc AMIA Symp. 2000:903-7.
10
Are antipsychotic drugs potentially chemopreventive agents for cancer?抗精神病药物有可能成为癌症的化学预防剂吗?
Eur J Clin Pharmacol. 1999 Aug;55(6):487-8. doi: 10.1007/s002280050661.

运用基于文献的发现范式来研究药物作用机制。

Using the literature-based discovery paradigm to investigate drug mechanisms.

作者信息

Ahlers Caroline B, Hristovski Dimitar, Kilicoglu Halil, Rindflesch Thomas C

机构信息

National Library of Medicine, Bethesda, MD, USA.

出版信息

AMIA Annu Symp Proc. 2007 Oct 11;2007:6-10.

PMID:18693787
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2655783/
Abstract

Drug therapies are often used effectively without their underlying mechanism being completely understood. We exploit the literature-based discovery paradigm to investigate these mechanisms and propose a discovery pattern that draws on semantic predications extracted from MEDLINE citations. The use of semantic predications and the discovery pattern provides a way to uncover previously unnoticed associations between pharmacologic and bioactive substances on the one hand and bioactive substances and disorders on the other. In this paper, we concentrate on research investigating the use of antipsychotic agents used for treatment of cancer. Our method resulted in five biomolecules that may provide a link between the antipsychotic agents and cancer: brain-derived neurotrophic factor, CYP2D6, glucocorticoid receptor, PRL, and TNF.

摘要

药物疗法常常能有效发挥作用,但其潜在机制却并未被完全理解。我们利用基于文献的发现范式来研究这些机制,并提出一种发现模式,该模式借鉴了从MEDLINE引用文献中提取的语义预测。语义预测和发现模式的使用提供了一种方法,一方面揭示药物和生物活性物质之间,另一方面揭示生物活性物质和疾病之间以前未被注意到的关联。在本文中,我们专注于研究用于治疗癌症的抗精神病药物的使用情况。我们的方法得出了五种生物分子,它们可能在抗精神病药物和癌症之间建立联系:脑源性神经营养因子、CYP2D6、糖皮质激素受体、催乳素和肿瘤坏死因子。