Suppr超能文献

[基于本体的神经信息学概念及其关系]

[Concepts of ontology-based neuroinformatics and their relations].

作者信息

Li Yi, Yu Jin-feng, Yin Ling, Cui Guang-zuo

机构信息

Department of Information Management, Peking University, Beijing 100871, China.

出版信息

Beijing Da Xue Xue Bao Yi Xue Ban. 2009 Apr 18;41(2):230-4.

Abstract

OBJECTIVE

To supply good information integration, knowledge representation, text mining, intellectual education and data sharing services by setting up neuroinformatics ontology.

METHODS

By analyzing the structures and contents of current ontologies in the biomedical field, such as UMLS, Gene Ontology, Cancer Ontology, Anatomy Ontology, Disease Ontology and Drug Ontology, the concepts and their relationships of neuroinformatics were discussed and the design principles, standards and norms, building methods and basic procedures of multi-level concept semantic networks-based neuroinformatics ontology constructed by Protege-OWL tool were presented in this article.

RESULTS

A multi-level concept semantic network-based OWL (web ontology language) neuroinformatics ontology was built.

CONCLUSION

The neuroinformatics ontology can bring about explicit definitions of concepts and their relationships in the field of neuroinformatics from different formal models, build clear theoretical framework for neuroinformatics, achieve a common understanding of related field knowledge and supply good services of information integration, knowledge representation, text mining, intelligent education and data sharing.

摘要

目的

通过建立神经信息学本体,提供良好的信息整合、知识表示、文本挖掘、智能教育和数据共享服务。

方法

通过分析生物医学领域当前本体(如统一医学语言系统、基因本体、癌症本体、解剖学本体、疾病本体和药物本体)的结构和内容,讨论神经信息学的概念及其关系,并介绍使用Protege-OWL工具构建基于多层次概念语义网络的神经信息学本体的设计原则、标准和规范、构建方法及基本流程。

结果

构建了基于多层次概念语义网络的OWL(网络本体语言)神经信息学本体。

结论

神经信息学本体能够从不同形式模型对神经信息学领域的概念及其关系进行明确界定,为神经信息学构建清晰的理论框架,实现对相关领域知识的共识,并提供良好的信息整合、知识表示、文本挖掘、智能教育和数据共享服务。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验