An integrated pharmacokinetics ontology and corpus for text mining

BMC Bioinformatics

Database

Shreyas Karnik¹  Heng-Yi Wu¹  Chienwei Chiang¹  Abhinita Subhadarshini¹  Zhiping Wang²  David Flockhart³  Lang Li⁴  Xu Han⁵  Santosh Philips⁶  Sara K Quinney⁷  Luis M Rocha⁸  Malaz Boustani⁹  Lei Liu^1,10 

[1] Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, USA;Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, USA;Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Pharmacology and Toxicology, School of Medicine, Indiana University, Indianapolis, IN, USA;Division of Clinical Pharmacology, School of Medicine, Indiana University, Indianapolis, IN, USA;Indiana Institute of Personalized Medicine, Indianapolis, IN, USA;Department of Obstetrics and Gynecology, School of Medicine, Indiana University, Indianapolis, IN, USA;Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, USA;Division of Clinical Pharmacology, School of Medicine, Indiana University, Indianapolis, IN, USA;Informatics and Cognitive Science Center for Complex Networks and Systems Research, School of Informatics & Computing, Indianapolis, IN, USA;Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Pharmacology and Toxicology, School of Medicine, Indiana University, Indianapolis, IN, USA;Division of Clinical Pharmacology, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Pharmacology and Toxicology, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Pharmacology and Toxicology, School of Medicine, Indiana University, Indianapolis, IN, USA;Department of Obstetrics and Gynecology, School of Medicine, Indiana University, Indianapolis, IN, USA;Informatics and Cognitive Science Center for Complex Networks and Systems Research, School of Informatics & Computing, Indianapolis, IN, USA;Regenstrief Institute, Indianapolis, IN, USA;Shanghai Center for Bioinformation and Technology, 200235, Shanghai, China;

关键词: Text Mining;    Annotation Scheme;    Drug Interaction Study;    GENIA Corpus;    Cascade Style Sheet;   

DOI  :  10.1186/1471-2105-14-35

 received in 2011-12-08, accepted in 2012-11-30,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundDrug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics data have been unevenly collected in different databases and published extensively in the literature. Without appropriate pharmacokinetics ontology and a well annotated pharmacokinetics corpus, it will be difficult to develop text mining tools for pharmacokinetics data collection from the literature and pharmacokinetics data integration from multiple databases.DescriptionA comprehensive pharmacokinetics ontology was constructed. It can annotate all aspects of in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. It covers all 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.ConclusionsThe 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.

【 授权许可】

Unknown   
© Wu et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.