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MPI-LIT: a literature-curated dataset of microbial binary protein--protein interactions

机译:MPI-LIT:微生物二元蛋白质-蛋白质相互作用的文献精选数据集

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Prokaryotic protein–protein interactions are underrepresented in currently available databases. Here, we describe a ‘gold standard’ dataset (MPI-LIT) focusing on microbial binary protein–protein interactions and associated experimental evidence that we have manually curated from 813 abstracts and full texts that were selected from an initial set of 36 852 abstracts. The MPI-LIT dataset comprises 1237 experimental descriptions that describe a non-redundant set of 746 interactions of which 659 (88%) are not reported in public databases. To estimate the curation quality, we compared our dataset with a union of microbial interaction data from IntAct, DIP, BIND and MINT. Among common abstracts, we achieve a sensitivity of up to 66% for interactions and 75% for experimental methods. Compared with these other datasets, MPI-LIT has the lowest fraction of interaction experiments per abstract (0.9) and the highest coverage of strains (92) and scientific articles (813). We compared methods that evaluate functional interactions among proteins (such as genomic context or co-expression) which are implemented in the STRING database. Most of these methods discriminate well between functionally relevant protein interactions (MPI-LIT) and high-throughput data.
机译:在现有数据库中,原核蛋白之间的相互作用不足。在这里,我们描述了一个“黄金标准”数据集(MPI-LIT),重点是微生物二元蛋白质-蛋白质相互作用以及相关的实验证据,这些证据是我们从813篇摘要和从36 852篇摘要的初始集合中选择的全文中手动挑选出来的。 MPI-LIT数据集包含1237个实验描述,这些描述描述了746个交互的非冗余集合,其中659个(88%)未在公共数据库中报告。为了评估策展质量,我们将数据集与来自IntAct,DIP,BIND和MINT的微生物相互作用数据进行了比较。在常见摘要中,我们对交互的敏感性高达66%,对实验方法的敏感性高达75%。与其他数据集相比,MPI-LIT的每个摘要的交互作用试验的分数最低(0.9),菌株的覆盖率最高(92)和科学论文(813)。我们比较了评估STRING数据库中实现的蛋白质之间功能相互作用(例如基因组背景或共表达)的方法。这些方法大多数都能很好地区分功能相关的蛋白质相互作用(MPI-LIT)和高通量数据。

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