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胰腺表达数据库:2018 年更新。

The Pancreatic Expression Database: 2018 update.

机构信息

Bioinformatics Unit, Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University London, London EC1M 6BQ, UK.

Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University London, London EC1M 6BQ, UK.

出版信息

Nucleic Acids Res. 2018 Jan 4;46(D1):D1107-D1110. doi: 10.1093/nar/gkx955.

Abstract

The Pancreatic Expression Database (PED, http://www.pancreasexpression.org) continues to be a major resource for mining pancreatic -omics data a decade after its initial release. Here, we present recent updates to PED and describe its evolution into a comprehensive resource for extracting, analysing and integrating publicly available multi-omics datasets. A new analytical module has been implemented to run in parallel with the existing literature mining functions. This analytical module has been created using rich data content derived from pancreas-related specimens available through the major data repositories (GEO, ArrayExpress) and international initiatives (TCGA, GENIE, CCLE). Researchers have access to a host of functions to tailor analyses to meet their needs. Results are presented using interactive graphics that allow the molecular data to be visualized in a user-friendly manner. Furthermore, researchers are provided with the means to superimpose layers of molecular information to gain greater insight into alterations and the relationships between them. The literature-mining module has been improved with a redesigned web appearance, restructured query platforms and updated annotations. These updates to PED are in preparation for its integration with the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB), a vital resource of pancreas cancer tissue for researchers to support and promote cutting-edge research.

摘要

胰腺表达数据库(PED,http://www.pancreasexpression.org)自发布以来已有十年,一直是挖掘胰腺组学数据的主要资源。在这里,我们将介绍 PED 的最新更新,并描述其如何发展成为一个用于提取、分析和整合公共多组学数据集的综合资源。一个新的分析模块已与现有的文献挖掘功能并行实现。这个分析模块是使用从主要数据存储库(GEO、ArrayExpress)和国际计划(TCGA、GENIE、CCLE)中获取的与胰腺相关的样本中提取的丰富数据内容创建的。研究人员可以访问各种功能来定制分析以满足他们的需求。结果使用交互式图形呈现,允许以用户友好的方式可视化分子数据。此外,研究人员还可以通过叠加分子信息层来获得更多关于变化及其之间关系的深入了解。文献挖掘模块经过重新设计的网页外观、重新构建的查询平台和更新的注释进行了改进。这些 PED 更新是为了与胰腺癌症研究基金组织库(PCRFTB)集成做准备,PCRFTB 是一个宝贵的胰腺癌症组织资源,为研究人员提供支持和促进前沿研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5489/5753364/575518676980/gkx955fig1.jpg

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