LitInspector: literature and signal transduction pathway mining in PubMed abstracts.
LitInspector: literature and signal transduction pathway mining in PubMed abstracts.
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DOI：
10.1093/nar/gkp303
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发表时间：
2009-07
影响因子：
14.9
通讯作者：
Frech K
中科院分区：
文献类型：
--
作者：
Frisch M;Klocke B;Haltmeier M;Frech K
LitInspector 是一种文献检索工具，可在 NCBI 的 PubMed 数据库中进行基因和信号转导通路挖掘。自动基因识别和颜色编码提高了摘要的可读性，并显着加快了文献研究的速度。基因识别的主要挑战是解决同音异义词和拒绝“非基因”环境中使用的相同缩写。为此，LitInspector 使用自动生成和手动优化的过滤列表。 LitInspector 结果的质量通过已发布的包含 181 个 PubMed 句子的数据集进行评估。 LitInspector 的精确度为 96.8%，召回率为 86.6%，F 测量为 91.4%。为了进一步证明同音词解析质量，使用一些具有挑战性的示例将 LitInspector 与其他三个文献搜索工具进行了比较。 LitInspector 正确解析了 87% 的摘要中的同音异义 MIZ-1（基因 ID 7709 和 9063），而其他工具的识别率在 35% 到 67% 之间。 LitInspector 信号转导通路挖掘基于手动管理的通路名称数据库（例如 wingless 类型）、通路组件（例如 WNT1、FZD1）和一般通路关键字（例如信号级联）。检查 10 个随机选择的基因的性能。 38 个预测的通路关联中有 82% 是正确的。 LitInspector 可在 http://www.litinspector.org/ 上免费获取。
LitInspector is a literature search tool providing gene and signal transduction pathway mining within NCBI's PubMed database. The automatic gene recognition and color coding increases the readability of abstracts and significantly speeds up literature research. A main challenge in gene recognition is the resolution of homonyms and rejection of identical abbreviations used in a ‘non-gene’ context. LitInspector uses automatically generated and manually refined filtering lists for this purpose. The quality of the LitInspector results was assessed with a published dataset of 181 PubMed sentences. LitInspector achieved a precision of 96.8%, a recall of 86.6% and an F-measure of 91.4%. To further demonstrate the homonym resolution qualities, LitInspector was compared to three other literature search tools using some challenging examples. The homonym MIZ-1 (gene IDs 7709 and 9063) was correctly resolved in 87% of the abstracts by LitInspector, whereas the other tools achieved recognition rates between 35% and 67%. The LitInspector signal transduction pathway mining is based on a manually curated database of pathway names (e.g. wingless type), pathway components (e.g. WNT1, FZD1), and general pathway keywords (e.g. signaling cascade). The performance was checked for 10 randomly selected genes. Eighty-two per cent of the 38 predicted pathway associations were correct. LitInspector is freely available at http://www.litinspector.org/.