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miRSel：从生物医学文献中自动提取 microRNA 和基因之间关联的方法。

miRSel: automated extraction of associations between microRNAs and genes from the biomedical literature.

机构信息

Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstr, 17 80333 München, Germany.

出版信息

BMC Bioinformatics. 2010 Mar 16;11:135. doi: 10.1186/1471-2105-11-135.

DOI:10.1186/1471-2105-11-135
PMID:20233441
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2845581/
Abstract

BACKGROUND

MicroRNAs have been discovered as important regulators of gene expression. To identify the target genes of microRNAs, several databases and prediction algorithms have been developed. Only few experimentally confirmed microRNA targets are available in databases. Many of the microRNA targets stored in databases were derived from large-scale experiments that are considered not very reliable. We propose to use text mining of publication abstracts for extracting microRNA-gene associations including microRNA-target relations to complement current repositories.

RESULTS

The microRNA-gene association database miRSel combines text-mining results with existing databases and computational predictions. Text mining enables the reliable extraction of microRNA, gene and protein occurrences as well as their relationships from texts. Thereby, we increased the number of human, mouse and rat miRNA-gene associations by at least three-fold as compared to e.g. TarBase, a resource for miRNA-gene associations.

CONCLUSIONS

Our database miRSel offers the currently largest collection of literature derived miRNA-gene associations. Comprehensive collections of miRNA-gene associations are important for the development of miRNA target prediction tools and the analysis of regulatory networks. miRSel is updated daily and can be queried using a web-based interface via microRNA identifiers, gene and protein names, PubMed queries as well as gene ontology (GO) terms. miRSel is freely available online at http://services.bio.ifi.lmu.de/mirsel.

摘要

背景

MicroRNAs 已被发现是基因表达的重要调控因子。为了识别 microRNA 的靶基因，已经开发了几个数据库和预测算法。数据库中仅提供了少量经过实验验证的 microRNA 靶标。数据库中存储的许多 microRNA 靶标都来自被认为不太可靠的大规模实验。我们建议使用文献摘要的文本挖掘来提取 microRNA-基因关联，包括 microRNA-靶关系，以补充当前的存储库。

结果

microRNA-基因关联数据库 miRSel 将文本挖掘结果与现有数据库和计算预测相结合。文本挖掘能够可靠地从文本中提取 microRNA、基因和蛋白质的出现及其关系。因此，与 TarBase 等 miRNA-基因关联资源相比，我们将人类、小鼠和大鼠的 miRNA-基因关联数量至少增加了三倍。

结论

我们的数据库 miRSel 提供了目前最大的文献衍生 miRNA-基因关联集合。miRNA-基因关联的综合收集对于 miRNA 靶标预测工具的开发和调控网络的分析非常重要。miRSel 每天都会更新，并可以通过基于网络的界面使用 microRNA 标识符、基因和蛋白质名称、PubMed 查询以及基因本体 (GO) 术语进行查询。miRSel 可免费在线获得，网址为 http://services.bio.ifi.lmu.de/mirsel。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2073/2845581/d88bab42f118/1471-2105-11-135-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2073/2845581/e44eda73cb4c/1471-2105-11-135-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2073/2845581/1750d38ae83d/1471-2105-11-135-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2073/2845581/d88bab42f118/1471-2105-11-135-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2073/2845581/e44eda73cb4c/1471-2105-11-135-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2073/2845581/1750d38ae83d/1471-2105-11-135-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2073/2845581/d88bab42f118/1471-2105-11-135-3.jpg

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