SR4GN: a species recognition software tool for gene normalization.

SR4GN: a species recognition software tool for gene normalization.
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DOI:
10.1371/journal.pone.0038460
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Lu Z
Lu Z
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Wei CH;Kao HY;Lu Z

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正如最近的研究表明,物种识别和消歧是许多下游文本挖掘应用(例如基因标准化任务和蛋白质-蛋白质相互作用提取)中最关键和最具挑战性的步骤之一。我们报告 SR4GN:一种用于生物医学文本中物种识别和消歧的开源工具。除了现有工具中的物种检测功能外,SR4GN还针对基因标准化任务进行了优化。因此,它被开发用于将检测到的物种与文档中提及的相应基因联系起来。 SR4GN 的准确率达到 85.42%,在基准实验中与其他最先进的技术相比毫不逊色。最后,SR4GN 作为独立的软件工具实现,从而使其在许多文本挖掘应用程序中使用起来方便且强大。 SR4GN 可在以下网址下载:http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/downloads/SR4GN
As suggested in recent studies, species recognition and disambiguation is one of the most critical and challenging steps in many downstream text-mining applications such as the gene normalization task and protein-protein interaction extraction. We report SR4GN: an open source tool for species recognition and disambiguation in biomedical text. In addition to the species detection function in existing tools, SR4GN is optimized for the Gene Normalization task. As such it is developed to link detected species with corresponding gene mentions in a document. SR4GN achieves 85.42% in accuracy and compares favorably to the other state-of-the-art techniques in benchmark experiments. Finally, SR4GN is implemented as a standalone software tool, thus making it convenient and robust for use in many text-mining applications. SR4GN can be downloaded at: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/downloads/SR4GN
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