From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.
From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.
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DOI：
10.1186/s13637-017-0059-z
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发表时间：
2017-12
期刊：
影响因子：
--
通讯作者：
Di Silvestre D
中科院分区：
文献类型：
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作者：
Vella D;Zoppis I;Mauri G;Mauri P;Di Silvestre D
将生物系统分解成其组成部分的还原论方法在分子生物学的第一阶段已经成功地阐明了几个生物过程的化学基础。这些知识帮助生物学家理解了生物系统的复杂性，证明了大多数生物功能并不是由单个分子产生的;因此，认识到生物系统的涌现特性不能通过研究单个分子而不考虑它们之间的关系来解释或预测。由于当前组学技术的改进和对分子关系的理解的增加，更多的研究通过基于图论的方法来评估生物系统。基因组和蛋白质组数据通常与蛋白质-蛋白质相互作用（PPI）网络相结合，PPI网络的结构通常通过算法和工具进行分析，以表征枢纽/瓶颈以及拓扑、功能和疾病模块。另一方面，共表达网络代表了一种补充程序，它提供了在系统水平进行评估的机会，包括缺乏PPI信息的生物体。基于这些前提，我们向读者介绍PPI和共表达网络，包括重建和分析方面。特别是，通过共表达网络评估大规模蛋白质组数据的新想法将被讨论，并给出一些应用实例。他们的使用推断生物知识将显示，并将特别关注的拓扑和模块分析。
The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.