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UniProt-Related Documents (UniReD): assisting wet lab biologists in their quest on finding novel counterparts in a protein network

机译:UniProt相关的文件(UILifired):协助湿实验室生物学家在寻求在蛋白质网络中寻找新的对应物

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摘要

The in-depth study of protein–protein interactions (PPIs) is of key importance for understanding how cells operate. Therefore, in the past few years, many experimental as well as computational approaches have been developed for the identification and discovery of such interactions. Here, we present UniReD, a user-friendly, computational prediction tool which analyses biomedical literature in order to extract known protein associations and suggest undocumented ones. As a proof of concept, we demonstrate its usefulness by experimentally validating six predicted interactions and by benchmarking it against public databases of experimentally validated PPIs succeeding a high coverage. We believe that UniReD can become an important and intuitive resource for experimental biologists in their quest for finding novel associations within a protein network and a useful tool to complement experimental approaches (e.g. mass spectrometry) by producing sorted lists of candidate proteins for further experimental validation. UniReD is available at http://bioinformatics.med.uoc.gr/unired/
机译:对蛋白质 - 蛋白质相互作用(PPI)的深入研究是了解细胞如何运作的关键重要性。因此,在过去几年中,已经开发了许多实验以及计算方法来识别和发现这种相互作用。这里,我们提供了一个Unifired,一种用户友好的计算预测工具,其分析了生物医学文献,以提取已知的蛋白质关联并表明未记录的蛋白质联合。作为概念证明,我们通过通过通过实验验证六个预测的互动并通过对实验验证的PPI的公共数据库进行基准测试来展示其有用性,并通过高度覆盖。我们认为,由于通过生产用于进一步的实验验证的分选清单,可以成为寻求在蛋白质网络中寻找新颖的关联的重要和直观的实验生物学家资源,并通过生产用于进一步的实验验证的分选蛋白的分类列表来获得蛋白质网络中的新缔合品(例如质谱)(例如,质谱)。 Unired可在http://bioinformatics.med.uoc.gr/unired/

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