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LTMap:一个通过全基因组转录表达数据评估潜在肝脏毒性的网络服务器。

LTMap: a web server for assessing the potential liver toxicity by genome-wide transcriptional expression data.

作者信息

Xing Li, Wu Leihong, Liu Yufeng, Ai Ni, Lu Xiaoyan, Fan Xiaohui

机构信息

Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.

出版信息

J Appl Toxicol. 2014 Jul;34(7):805-9. doi: 10.1002/jat.2923. Epub 2013 Sep 11.

Abstract

Toxicogenomics (TGx) has played a significant role in mechanistic research related with hepatotoxicity as well as liver toxicity prediction. Currently, several large-scale preclinical TGx data sets were made freely accessible to the public, such as Open TG-GATEs. With the availability of a sufficient amount of microarray data, it is important to integrate this information to provide new insights into the risk assessment of potential drug-induced liver toxicity. Here we developed a web server for evaluating the potential liver toxicity based on genome-wide transcriptomics data, namely LTMap. In LTMap, researchers could compare signatures of query compounds against a pregenerated signature database of 20 123 Affymetrix arrays associated with about 170 compounds retrieved from the largest public toxicogenomics data set Open TG-GATEs. Results from this comparison may lead to the unexpected discovery of similar toxicological responses between chemicals. We validated our computational approach for similarity comparison using three example drugs. Our successful applications of LTMap in these case studies demonstrated its utility in revealing the connection of chemicals according to similar toxicological behaviors. Furthermore, a user-friendly web interface is provided by LTMap to browse and search toxicogenomics data (http://tcm.zju.edu.cn/ltmap).

摘要

毒理基因组学(TGx)在与肝毒性相关的机制研究以及肝脏毒性预测方面发挥了重要作用。目前,有几个大规模的临床前TGx数据集已向公众免费开放,比如开放毒理基因组学全球评估数据库(Open TG-GATEs)。随着大量微阵列数据的可得性,整合这些信息对于深入了解潜在药物性肝毒性的风险评估具有重要意义。在此,我们开发了一个基于全基因组转录组学数据评估潜在肝脏毒性的网络服务器,即肝毒性图谱(LTMap)。在LTMap中,研究人员可以将查询化合物的特征与一个预先生成的包含20123个Affymetrix阵列的特征数据库进行比较,该数据库与从最大的公共毒理基因组学数据集Open TG-GATEs中检索到的约170种化合物相关。这种比较的结果可能会意外发现化学物质之间相似的毒理学反应。我们使用三种示例药物验证了我们用于相似性比较的计算方法。我们在这些案例研究中成功应用LTMap证明了其在根据相似毒理学行为揭示化学物质之间联系方面的实用性。此外,LTMap提供了一个用户友好的网络界面来浏览和搜索毒理基因组学数据(http://tcm.zju.edu.cn/ltmap)。

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