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A text mining approach to detect mentions of protein glycosylation in biomedical text

机译:一种文本挖掘方法用于检测生物医学文本中蛋白质糖基化的提及

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摘要

Protein Glycosylation is an important post translational event that plays a pivotal role in protein folding and protein is trafficking. We describe a dictionary based and a rule based approach to mine ‘mentions‘ of protein glycosylation in text. The dictionary based approach relies on a set of manually curated dictionaries specially constructed to address this task. Abstracts are then screened for the ‘mentions‘ of words from these dictionaries which are further scored followed by classification on the basis of a threshold. The rule based approaches also relies on the words in the dictionary to arrive at the features which are used for classification. The performance of the system using both the approaches has been evaluated using a manually curated corpus of 3133 abstracts. The evaluation suggests that the performance of the Rule based approach supersedes that of the Dictionary based approach.
机译:蛋白质糖基化是重要的翻译后事件,在蛋白质折叠和蛋白质运输中起关键作用。我们描述了一种基于字典和基于规则的方法来挖掘文本中蛋白质糖基化的“提法”。基于字典的方法依赖于一组专门为解决此任务而精心设计的手动词典。然后从这些词典中筛选摘要中单词的“提法”,然后对其进一步打分,然后根据阈值进行分类。基于规则的方法还依赖于词典中的单词来得出用于分类的特征。使用手动编制的3133个摘要的语料库评估了使用这两种方法的系统的性能。评估表明,基于规则的方法的性能优于基于字典的方法的性能。

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