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Ontology-based information extraction of regulatory networks from scientific articles with case studies for Escherichia coli

机译:从带有大肠杆菌案例研究的科学文章中基于本体论的监管网络信息提取

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摘要

The amount of scientific papers in the Molecular Biology field has experienced an enormous growth in the last years, prompting the need of developing automatic Information Extraction (IE) systems. This work is a first step towards the ontology-based domain-independent generalization of a system that identifies Escherichia coli regulatory networks. First, a domain ontology based on the RegulonDB database was designed and populated. After that, the steps of the existing IE system were generalized to use the knowledge contained in the ontology, so that it could be potentially applied to other domains. The resulting system has been tested both with abstract and full articles that describe regulatory interactions for £ coli, obtaining satisfactory results.
机译:近年来,分子生物学领域的科学论文数量经历了巨大的增长,这促使人们需要开发自动信息提取(IE)系统。这项工作是朝着基于本体的域独立性概括识别大肠杆菌调控网络的系统的第一步。首先,设计并填充了基于RegulonDB数据库的领域本体。此后,将现有IE系统的步骤推广到使用本体中包含的知识,以便可以将其潜在地应用于其他领域。所得系统已用摘要和完整的文章进行了测试,这些文章描述了针对大肠杆菌的调节相互作用,获得了令人满意的结果。

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