PROGgene:基于基因表达的多种癌症生存分析web应用程序。

Chirayu Pankaj Goswami, Harikrishna Nakshatri
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引用次数: 131

摘要

背景:各种癌症类型的预后mRNA生物标志物的鉴定已经完成。从这些研究中发表的数据存档在公共存储库中。在公共存储库中有数百个针对多种癌症类型的此类数据集。丰富的此类数据可用于研究mRNA在不同癌症以及同一癌症的不同人群或亚型中的预后意义。描述:我们创建了一个web应用程序,可用于研究mRNA生物标志物在各种癌症中的预后含义。我们从GEO、EBI Array Express和The Cancer Genome Atlas等公共存储库中编译了数据来创建这个工具。我们的数据库中有来自18种癌症类型的64个患者系列,该工具为迄今为止的生存分析提供了最全面的资源。该工具名为PROGgene,可在http://www.compbio.iupui.edu/proggene.Conclusions:上获得。我们将该工具作为假设生成工具,供研究人员识别潜在的预后mRNA生物标志物,以进行进一步的研究。出于这个原因,我们保持了web应用程序非常简单和直接。我们相信该工具将有助于加速癌症生物标志物的发现,并迅速提供可能表明特定生物标志物的疾病特异性预后价值的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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PROGgene: gene expression based survival analysis web application for multiple cancers.

Background: Identification of prognostic mRNA biomarkers has been done for various cancer types. The data that are published from such studies are archived in public repositories. There are hundreds of such datasets available for multiple cancer types in public repositories. Wealth of such data can be utilized to study prognostic implications of mRNA in different cancers as well as in different populations or subtypes of same cancer.

Description: We have created a web application that can be used for studying prognostic implications of mRNA biomarkers in a variety of cancers. We have compiled data from public repositories such as GEO, EBI Array Express and The Cancer Genome Atlas for creating this tool. With 64 patient series from 18 cancer types in our database, this tool provides the most comprehensive resource available for survival analysis to date. The tool is called PROGgene and it is available at http://www.compbio.iupui.edu/proggene.

Conclusions: We present this tool as a hypothesis generation tool for researchers to identify potential prognostic mRNA biomarkers to follow up with further research. For this reason, we have kept the web application very simple and straightforward. We believe this tool will be useful in accelerating biomarker discovery in cancer and quickly providing results that may indicate disease-specific prognostic value of specific biomarkers.

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