首页> 外文会议>Advanced Information Networking and Applications Workshops, 2009. WAINA '09 >Knowledge Extraction and Extrapolation Using Ancient and Modern Biomedical Literature
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Knowledge Extraction and Extrapolation Using Ancient and Modern Biomedical Literature

机译:利用古代和现代生物医学文献进行知识提取和外推

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Extraction of knowledge from biomedical literature is one of the major problems for researchers. This primarily involves identification of novel associations between biological objects (genes, proteins, diseases, medicines etc.). These associations are commonly extracted by mining biomedical resources such as the PUBMED which contains a large volume of information. An automated approach towards this end will reduce a substantial amount of time for biomedical researchers. In this paper we discuss a methodology to extract such associations and to assign a significance measure to the generated hypotheses. The computed significance value for the extracted knowledge can be considered as association strength between biological objects. The generated hypotheses with large significance can be considered for further experimental validation by biologists. In this paper we conduct two different validation studies of the results, which provide justification for the approach that was followed to generate the hypotheses.
机译:从生物医学文献中提取知识是研究人员的主要问题之一。这主要涉及鉴定生物学对象(基因,蛋白质,疾病,药物等)之间的新型关联。通常通过挖掘生物医学资源(例如包含大量信息的PUBMED)来提取这些关联。为此目的的自动化方法将减少生物医学研究人员的大量时间。在本文中,我们讨论了一种提取此类关联并为所产生的假设分配显着性度量的方法。所提取的知识的计算出的显着性值可以视为生物对象之间的关联强度。生物学家可以考虑所产生的具有重大意义的假设,以进行进一步的实验验证。在本文中,我们对结果进行了两次不同的验证研究,这些研究为产生假设所采用的方法提供了依据。

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