首页> 美国卫生研究院文献>Journal of Korean Medical Science >Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses
【2h】

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

机译:使用宿主反应的DNA微阵列基因表达谱预测培养细胞的微生物感染

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, , , , , and . In addition, we discovered two of these genes, , and , are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection ().
机译:在基于细胞培养的生物学研究中,微生物感染可能导致致命的错误解释。细胞培养物中微生物的污染非常频繁(5%至35%)。然而,当前用于识别污染的存在的方法具有许多局限性,例如高昂的时间和人工成本,以及难以解释结果。在本文中,我们提出了一种使用微阵列技术预测细胞感染的模型,该技术提供了整个基因组概况的概述。通过在各种实验条件下改变细胞类型,感染来源和收集时间的62种微阵列表达谱分析,我们发现了5个标记基因,,,和。此外,我们发现了其中的两个基因和参与了支原体特异性感染过程。我们还建议使用模型来预测感染的来源,细胞类型或感染后的时间。我们在微阵列数据中实现了一个基于Web的预测工具,称为微生物感染预测()。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号