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Confirmation of human protein interaction data by human expression data

机译:通过人类表达数据确认人类蛋白质相互作用数据

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Background With microarray technology the expression of thousands of genes can be measured simultaneously. It is well known that the expression levels of genes of interacting proteins are correlated significantly more strongly in Saccharomyces cerevisiae than those of proteins that are not interacting. The objective of this work is to investigate whether this observation extends to the human genome. Results We investigated the quantitative relationship between expression levels of genes encoding interacting proteins and genes encoding random protein pairs. Therefore we studied 1369 interacting human protein pairs and human gene expression levels of 155 arrays. We were able to establish a statistically significantly higher correlation between the expression levels of genes whose proteins interact compared to random protein pairs. Additionally we were able to provide evidence that genes encoding proteins belonging to the same GO-class show correlated expression levels. Conclusion This finding is concurrent with the naive hypothesis that the scales of production of interacting proteins are linked because an efficient interaction demands that involved proteins are available to some degree. The goal of further research in this field will be to understand the biological mechanisms behind this observation.
机译:背景技术利用微阵列技术,可以同时测量数千种基因的表达。众所周知,在酿酒酵母中,相互作用蛋白的基因表达水平与不相互作用蛋白的表达水平显着相关。这项工作的目的是调查这种观察是否扩展到人类基因组。结果我们研究了编码相互作用蛋白的基因和编码随机蛋白对的基因的表达水平之间的定量关系。因此,我们研究了1369个相互作用的人类蛋白质对和155个阵列的人类基因表达水平。与随机的蛋白质对相比,我们能够在蛋白质相互作用的基因的表达水平之间建立统计学上显着更高的相关性。另外,我们能够提供证据证明编码属于同一GO类蛋白质的基因显示出相关的表达水平。结论这一发现与天真假说同时存在,天真假说认为相互作用蛋白的生产规模是相互联系的,因为有效的相互作用要求所涉及的蛋白在某种程度上是可用的。在该领域进一步研究的目的将是理解该观察背后的生物学机制。

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