Named entity recognition for bacterial Type IV secretion systems.
Named entity recognition for bacterial Type IV secretion systems.
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DOI：
10.1371/journal.pone.0014780
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发表时间：
2011-03-29
期刊：
影响因子：
3.7
通讯作者：
Sobral B
中科院分区：
文献类型：
--
作者：
Ananiadou S;Sullivan D;Black W;Levow GA;Gillespie JJ;Mao C;Pyysalo S;Kolluru B;Tsujii J;Sobral B
对专门生物系统的研究往往因缺乏一致的术语而受到阻碍，特别是跨物种的术语。在细菌IV型分泌系统中，一组直系同源物中的基因可能有十几个不同的名称。基于生物学过程、细胞组分、分子功能和微生物物种对研究出版物进行分类，可以提高文献检索的精确度和召回率，使研究人员能够通过病理系统资源整合中心（PATRIC，patricbrc.org）等资源跟上呈指数增长的文献。我们为与IV型分泌系统相关的四个实体开发了命名实体识别（NER）工具：1）细菌名称，2）生物过程，3）分子功能和4）细胞组分。这四个实体对致病机理和毒力研究很重要，但受到的关注少于其他实体，例如，基因和蛋白质。基于注释语料库，大型领域术语资源和机器学习技术，我们开发了这些实体的识别器。细菌、生物过程和分子功能的准确率高（>80%）。对比实验突出了替代识别策略的有效性;对比文档集上的术语提取结果证明了这些类用于识别T4 SS相关文档的实用性。
Research on specialized biological systems is often hampered by a lack of consistent terminology, especially across species. In bacterial Type IV secretion systems genes within one set of orthologs may have over a dozen different names. Classifying research publications based on biological processes, cellular components, molecular functions, and microorganism species should improve the precision and recall of literature searches allowing researchers to keep up with the exponentially growing literature, through resources such as the Pathosystems Resource Integration Center (PATRIC, patricbrc.org). We developed named entity recognition (NER) tools for four entities related to Type IV secretion systems: 1) bacteria names, 2) biological processes, 3) molecular functions, and 4) cellular components. These four entities are important to pathogenesis and virulence research but have received less attention than other entities, e.g., genes and proteins. Based on an annotated corpus, large domain terminological resources, and machine learning techniques, we developed recognizers for these entities. High accuracy rates (>80%) are achieved for bacteria, biological processes, and molecular function. Contrastive experiments highlighted the effectiveness of alternate recognition strategies; results of term extraction on contrasting document sets demonstrated the utility of these classes for identifying T4SS-related documents.
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影响因子：
3.7
作者：
Gillespie JJ;Ammerman NC;Dreher-Lesnick SM;Rahman MS;Worley MJ;Setubal JC;Sobral BS;Azad AF
通讯作者：
Azad AF
影响因子：
3
作者：
Jin Y;McDonald RT;Lerman K;Mandel MA;Carroll S;Liberman MY;Pereira FC;Winters RS;White PS
通讯作者：
White PS
生物公约概述：生物学信息提取的批判性评估。
影响因子：
3
作者：
Hirschman L;Yeh A;Blaschke C;Valencia A
通讯作者：
Valencia A
影响因子：
3.6
作者：
Hamilton, HL;Domínguez, NM;Dillard, JP
通讯作者：
Dillard, JP
DOI：
10.1038/nrmicro2218
发表时间：
2009-10
期刊：
Nature reviews. Microbiology
影响因子：
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作者：
通讯作者：
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