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挖掘人类植入窗期间子宫内膜基因时空表达的数据。

Data mining of spatial-temporal expression of genes in the human endometrium during the window of implantation.

机构信息

Institute of Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China.

出版信息

Reprod Sci. 2012 Oct;19(10):1085-98. doi: 10.1177/1933719112442248. Epub 2012 Aug 21.

Abstract

Previous studies of microarrays have produced mass data that are far from fully applied. To make full use of the available mass data and to avoid redundancy and unnecessary waste, we employed bioinformatics tools GeneSifter and Ingenuity Pathway Analysis (IPA) to mine and annotate 45 microarrays related to endometrium receptivity from GEO (Gene Expression Omnibus) database. In total, 1543 gene sets were found to express differentially, of which 148 highly regulated genes were listed as potential biomarkers of the receptive endometrium. The function and pathway analysis identified the differentially expressed genes primarily involved in immune response and cell cycle. Two networks related to the cardiovascular system and cancers were generated within the genes which changed more than 10-fold. Nine genes were validated by real-time polymerase chain reaction. It was a meaningful exploration of the existing data to acquire useful and reliable information, and our results undoubtedly provided valuable clues for further studies.

摘要

先前的微阵列研究产生了大量的数据,但远未得到充分应用。为了充分利用现有的大量数据,并避免冗余和不必要的浪费,我们使用生物信息学工具 GeneSifter 和 IPA(Ingenuity Pathway Analysis)从 GEO(基因表达综合数据库)数据库中挖掘和注释了 45 个与子宫内膜容受性相关的微阵列。总共发现了 1543 个差异表达的基因集,其中列出了 148 个高度调节的基因作为接受性子宫内膜的潜在生物标志物。功能和通路分析确定差异表达的基因主要参与免疫反应和细胞周期。在变化超过 10 倍的基因中生成了两个与心血管系统和癌症相关的网络。通过实时聚合酶链反应验证了 9 个基因。对现有数据进行有意义的探索,以获取有用和可靠的信息,我们的结果无疑为进一步的研究提供了有价值的线索。

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