Automatic ontology construction from the literature.

Automatic ontology construction from the literature.
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从文献中自动构建本体。

DOI:
10.11234/gi1990.13.201
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发表时间:
2002
期刊:
Genome informatics. International Conference on Genome Informatics
影响因子:
--
通讯作者:
A. Valencia
A. Valencia
中科院分区:
--
文献类型:
--
作者:
C. Blaschke;A. Valencia

文献摘要

参考文献

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相似文献

详细的分类、受控的词汇和有组织的术语在科学和技术的不同领域被广泛使用。它们在分子生物学中相对较新的引入对于基因组学分析和大规模蛋白质组学实验的进展至关重要。不幸的是,本体的构建,包括术语,分类和实体关系,需要相当大的努力,包括大量的文献分析。我们在这里提出了一种方法,自动生成分类的基因产品功能使用书目信息。相应的分类结构反映了人类专家构建的分类结构。为酵母基因产物构建的大型结构的分析,以及对各种实例的详细检查,显示出令人鼓舞的特性。特别是,与广为接受的GO本体的比较指向不同的情况,其中自动导出的分类可以用于辅助人类专家注释本体。
Detailed classifications, controlled vocabularies and organised terminology are widely used in different areas of science and technology. Their relatively recent introduction in molecular biology has been crucial for progress in the analysis of genonics and massive proteomics experiments. Unfortunately the construction of the ontologies, including terminology, classification and entity relations requires considerable effort, including the analysis of massive amounts of literature. We propose here a method that automatically generates classifications of gene-product functions using bibliographic information. The corresponding classification structures mirror the ones constructed by human experts. The analysis of a large structure built for yeast gene-products, and the detailed inspection of various examples, show encouraging properties. In particular, the comparison with the well accepted GO ontology points to different situations in which the automatically derived classification can be useful for assisting human experts in the annotation of ontologies.
使用统一医学语言系统的知识表示和索引。
DOI: 10.1142/9789814447331_0047
发表时间: 2000
影响因子: --
作者:
Baclawski,K;Cigna,J;Kokar,MM;Mager,P;Indurkhya,B
通讯作者: Indurkhya,B
DOI: 10.1101/gr.199701
发表时间: 2002-01-01
期刊: GENOME RESEARCH
影响因子: 7
作者:
Raychaudhuri, S;Chang, JT;Altman, RB
通讯作者: Altman, RB
DOI: --
发表时间: 2000
期刊: Proceedings. AMIA Symposium
影响因子: --
作者:
Qi Li;Philip Shilane;Natasha Noy;M. Musen
通讯作者: Qi Li;Philip Shilane;Natasha Noy;M. Musen