SciMiner: web-based literature mining tool for target identification and functional enrichment analysis.
SciMiner: web-based literature mining tool for target identification and functional enrichment analysis.
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DOI：
10.1093/bioinformatics/btp049
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发表时间：
2009-03-15
期刊：
影响因子：
--
通讯作者：
Feldman EL
中科院分区：
文献类型：
--
作者：
Hur J;Schuyler AD;States DJ;Feldman EL
摘要：SciMiner是一种基于网络的文献挖掘和功能分析工具，它通过对MEDLINE摘要和全文进行特定情境分析来识别基因和蛋白质。SciMiner接受自由文本查询（PubMed Entrez搜索）或PubMed标识符列表作为输入。SciMiner同时使用正则表达式模式以及从多个来源汇编的基因符号和名称词典。通过基于首字母缩写词和相应描述术语共现的评分方案来解决有歧义的首字母缩写词，该方案包含可选的用户定义过滤器。功能富集分析用于通过将一次搜索结果中识别的目标与其他搜索结果中的目标或与整个HGNC（人类基因组组织基因命名委员会）基因集进行比较，来识别高度相关的目标（基因和蛋白质）、GO（基因本体论）术语、MeSH（医学主题词）术语、通路以及蛋白质 - 蛋白质相互作用网络。基因/蛋白质名称识别的性能以BioCreAtIvE（生物学信息提取系统的关键评估）第2版（2006年）基因归一化任务作为金标准进行评估。SciMiner的召回率达到87.1%，准确率达到71.3%，F值达到75.8%。SciMiner的文献挖掘性能与功能富集分析相结合，为从用户感兴趣的文献集中检索和总结丰富的生物信息提供了一个高效的平台。
可用性：http://jdrf.neurology.med.umich.edu/SciMiner/。SciMiner的服务器版本也可供下载，使用户能够利用其所在机构的期刊订阅。
联系人：juhur@umich.edu
补充信息：补充数据可在Bioinformatics在线获取。
Summary:SciMiner is a web-based literature mining and functional analysis tool that identifies genes and proteins using a context specific analysis of MEDLINE abstracts and full texts. SciMiner accepts a free text query (PubMed Entrez search) or a list of PubMed identifiers as input. SciMiner uses both regular expression patterns and dictionaries of gene symbols and names compiled from multiple sources. Ambiguous acronyms are resolved by a scoring scheme based on the co-occurrence of acronyms and corresponding description terms, which incorporates optional user-defined filters. Functional enrichment analyses are used to identify highly relevant targets (genes and proteins), GO (Gene Ontology) terms, MeSH (Medical Subject Headings) terms, pathways and protein–protein interaction networks by comparing identified targets from one search result with those from other searches or to the full HGNC [HUGO (Human Genome Organization) Gene Nomenclature Committee] gene set. The performance of gene/protein name identification was evaluated using the BioCreAtIvE (Critical Assessment of Information Extraction systems in Biology) version 2 (Year 2006) Gene Normalization Task as a gold standard. SciMiner achieved 87.1% recall, 71.3% precision and 75.8% F-measure. SciMiner's literature mining performance coupled with functional enrichment analyses provides an efficient platform for retrieval and summary of rich biological information from corpora of users' interests. Availability: http://jdrf.neurology.med.umich.edu/SciMiner/. A server version of the SciMiner is also available for download and enables users to utilize their institution's journal subscriptions. Contact: juhur@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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