GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique.
GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique.
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GapsCreener：使用支持向量机技术在PubMed筛选人类遗传关联文献的自动工具。
DOI：
10.1186/1471-2105-9-205
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发表时间：
2008-04-22
影响因子：
3
通讯作者：
Gwinn M
中科院分区：
文献类型：
--
作者：
Yu W;Clyne M;Dolan SM;Yesupriya A;Wulf A;Liu T;Khoury MJ;Gwinn M
从已发表的人类遗传关联研究中合成数据是将人类基因组发现转化为健康应用的关键一步。虽然遗传关联研究占PubMed摘要的很大一部分，但用标准查询识别它们并不总是准确或有效的。进一步自动化文献筛选过程可以减轻劳动密集型和耗时的传统文献检索的负担。支持向量机（SVM）是一种成熟的机器学习技术，已成功地对包括生物医学文献在内的文本进行分类。GAPscreener是一种基于SVM的免费软件工具，可用于协助筛选PubMed摘要以进行人类遗传关联研究。本研究的数据源是HuGE Navigator，以前称为HuGE Pub Lit数据库。基于双向z得分方法获得的关键字列表的加权SVM特征选择表现出最好的筛选性能，在性能测试中达到97.5%的召回率，98.3%的特异性和31.9%的精确度。与基于复杂PubMed查询的传统筛选过程相比，SVM工具将需要数据库管理员单独审查的摘要数量减少了约90%。该工具还确定了47篇在4周测试期间被传统文献筛选过程遗漏的文章。我们以早产为例，研究了遗传相关的文献。与传统的手动过程相比，GAPscreener既减少了工作量又提高了准确性。GAPscreener是第一个免费的基于SVM的应用程序，可用于筛选PubMed中的人类遗传关联文献，具有高召回率和特异性。用户友好的图形用户界面使其成为实用的独立应用程序。该软件可以免费下载。
Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM), a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge.
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影响因子：
5.8
作者：
Ng, Kwang Loong Stanley;Mishra, Santosh K.
通讯作者：
Mishra, Santosh K.
影响因子：
3
作者：
Rice SB;Nenadic G;Stapley BJ
通讯作者：
Stapley BJ
影响因子：
5
作者：
Lin, Bruce K.;Clyne, Melinda;Khoury, Muin J.
通讯作者：
Khoury, Muin J.
影响因子：
3
作者：
Donaldson, I;Martin, J;de Bruijn, B;Wolting, C;Lay, V;Tuekam, B;Zhang, SD;Baskin, B;Bader, GD;Michalickova, K;Pawson, T;Hogue, CWV
通讯作者：
Hogue, CWV
影响因子：
5
作者：
Ioannidis, JPA;Bernstein, J;Khoury, MJ
通讯作者：
Khoury, MJ