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CrossCheck:一个用于高通量筛选数据分析的开源网络工具。

CrossCheck: an open-source web tool for high-throughput screen data analysis.

机构信息

Department of Computer Engineering, Faculty of Engineering, Gazi University, Ankara, Turkey.

Department of Cell Biology, Harvard Medical School, Boston, USA.

出版信息

Sci Rep. 2017 Jul 19;7(1):5855. doi: 10.1038/s41598-017-05960-3.

Abstract

Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

摘要

现代高通量筛选方法使研究人员能够生成包含重要生物学信息的大型数据集。然而,通常情况下,从这些筛选中挑选相关的命中并生成可测试的假设需要在生物信息学方面进行培训,并且需要具备高效执行数据库挖掘的技能。目前还没有可供公众使用的工具,允许用户将他们的筛选数据集与已发表的筛选数据集进行交叉参考。为此,我们开发了 CrossCheck,这是一个用于高通量筛选数据分析的在线平台。CrossCheck 是一个集中式数据库,允许用户轻松地将输入的基因符号列表与 16231 个已发表的数据集进行比较。这些数据集包括来自全基因组 RNAi 和 CRISPR 筛选、相互作用组蛋白质组学和磷酸蛋白质组学筛选、癌症突变数据库、主要细胞信号转导介质(如激酶、E3 泛素连接酶和磷酸酶)的低通量研究以及基因本体论信息的已发表数据。此外,CrossCheck 还包含一个新的预测蛋白激酶底物数据库,该数据库是使用全蛋白质组共识基序搜索开发的。CrossCheck 极大地简化了高通量筛选数据分析,使研究人员能够深入挖掘已发表的文献,并简化数据驱动的假设生成。CrossCheck 可作为基于网络的应用程序免费访问,网址为 http://proteinguru.com/crosscheck。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40e8/5517520/f2f8f16aa199/41598_2017_5960_Fig1_HTML.jpg

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