期刊
CHEMICAL REVIEWS
卷 117, 期 12, 页码 7673-7761出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.chemrev.6b00851
关键词
-
资金
- European Community's Horizon 2020 Program [654021 - OpenMinted]
- Conselleria de Cultura, Educacion e Ordenacion Universitaria (Xunta de Galicia)
- FEDER (European Union)
- Portuguese Foundation for Science and Technology (FCT) [UID/BIO/04469/2013 unit, POCI-01-0145-FEDER-006684]
Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据