Text mining for drug-drug interaction.
Text mining for drug-drug interaction.
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DOI：
10.1007/978-1-4939-0709-0_4
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Li L
中科院分区：
文献类型：
--
作者：
Wu HY;Chiang CW;Li L
为了更好地了解药物相互作用（DDI）的机制，药物动力学（PK）、药效学（PD）和药物遗传学（PG）数据的研究具有重要意义。近年来，药物PK参数、药物相互作用参数和PG数据在不同数据库中的收集不均匀，并在文献中广泛发表。此外，缺乏适当的PK本体和注释良好的PK语料库，分别提供背景知识和确定DDI的标准，导致难以开发DDI文本挖掘工具，用于从文献中收集PK数据和从多个数据库中集成数据。为了克服这些问题，我们构建了一个全面的药代动力学本体。它包括体外药代动力学实验、体内药代动力学研究以及药物代谢和转运酶的各个方面。使用我们的药代动力学本体，PK语料库的构建，目前四类药代动力学摘要：在体内药代动力学研究，在体内药物遗传学研究，在体内药物相互作用研究，在体外药物相互作用研究。提出并实现了一种新的分层三级标注方案，用于标注关键词、药物相互作用句子和药物相互作用对。药代动力学本体的效用通过注释三个药代动力学研究来证明;药代动力学语料库的效用通过药物相互作用提取文本挖掘分析来证明。药代动力学本体诠释了体外药代动力学实验和体内药代动力学研究。PK语料库是药代动力学参数和药物相互作用的文本挖掘的非常有价值的资源。
In order to understand the mechanisms of drug–drug interaction (DDI), the study of pharmacokinetics (PK), pharmacodynamics (PD), and pharmacogenetics (PG) data are significant. In recent years, drug PK parameters, drug interaction parameters, and PG data have been unevenly collected in different databases and published extensively in literature. Also the lack of an appropriate PK ontology and a well-annotated PK corpus, which provide the background knowledge and the criteria of determining DDI, respectively, lead to the difficulty of developing DDI text mining tools for PK data collection from the literature and data integration from multiple databases. To conquer the issues, we constructed a comprehensive pharmacokinetics ontology. It includes all aspects of in vitro pharmacokinetics experiments, in vivo pharmacokinetics studies, as well as drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three-level annotation scheme was proposed and implemented to tag key terms, drug interaction sentences, and drug interaction pairs. The utility of the pharmacokinetics ontology was demonstrated by annotating three pharmacokinetics studies; and the utility of the PK corpus was demonstrated by a drug interaction extraction text mining analysis. The pharmacokinetics ontology annotates both in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. The PK corpus is a highly valuable resource for the text mining of pharmacokinetics parameters and drug interactions.
影响因子：
2.5
作者：
Zhou, Jihao;Qin, Zhaohui;Quinney, Sara K.;Kim, Seongho;Wang, Zhiping;Yu, Menggang;Chien, Jenny Y.;Lucksiri, Aroonrut;Hall, Stephen D.;Li, Lang
通讯作者：
Li, Lang