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Unbiased ProteinAssociation Study on the Public HumanProteome Reveals Biological Connections between Co-Occurring ProteinPairs

机译:无偏蛋白公众人物协会研究蛋白质组揭示了共生蛋白之间的生物学联系对

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摘要

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targetsfor follow-up analysis.
机译:基于质谱的高通量蛋白质组学实验可产生大量数据。尽管通常获取这些数据来回答特定的生物学问题,但这些数据也可以以正交方式重复使用以揭示新的生物学知识。我们在这里提出了一种新的方法,用于公共蛋白质组学数据的此类正交数据重用。我们的方法基于PRIDE数据库中整个人类实验中这些蛋白质的共现,阐明了蛋白质之间的生物学关系。通过我们的方法检测到的大多数显着同时存在的蛋白质对已成功地映射到现有的生物学知识上。我们的新方法的有效性通过基于同一组蛋白质之间随机关联可以映射到现有知识的极少数对来证实。此外,使用文献搜索和STRING数据库,我们能够得出使用我们的方法检测到的未注释蛋白对的有意义的生物学关联,进一步说明了迄今未知的关联提出了非常有趣的目标进行后续分析。

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