Institute of Biomedical Technologies, National Research Council, Segrate (Milan), 20090, Italy.
Humanitas University, Department of Biomedical Sciences, Pieve Emanuele (Milan), 20090, Italy.
Brief Bioinform. 2021 Nov 5;22(6). doi: 10.1093/bib/bbab153.
The complex web of macromolecular interactions occurring within cells-the interactome-is the backbone of an increasing number of studies, but a clear consensus on the exact structure of this network is still lacking. Different genome-scale maps of human interactome have been obtained through several experimental techniques and functional analyses. Moreover, these maps can be enriched through literature-mining approaches, and different combinations of various 'source' databases have been used in the literature. It is therefore unclear to which extent the various interactomes yield similar results when used in the context of interactome-based approaches in network biology. We compared a comprehensive list of human interactomes on the basis of topology, protein complexes, molecular pathways, pathway cross-talk and disease gene prediction. In a general context of relevant heterogeneity, our study provides a series of qualitative and quantitative parameters that describe the state of the art of human interactomes and guidelines for selecting interactomes in future applications.
细胞内发生的大分子相互作用的复杂网络——相互作用组——是越来越多研究的基础,但对于这个网络的确切结构仍缺乏明确的共识。通过几种实验技术和功能分析已经获得了不同的人类相互作用组全基因组图谱。此外,这些图谱可以通过文献挖掘方法进行富集,并且在文献中使用了不同的各种“源”数据库的组合。因此,当在网络生物学中的基于相互作用组的方法的上下文中使用时,各种相互作用组在多大程度上产生相似的结果尚不清楚。我们基于拓扑结构、蛋白质复合物、分子途径、途径串扰和疾病基因预测,比较了一份全面的人类相互作用组清单。在相关异质性的一般背景下,我们的研究提供了一系列定性和定量参数,描述了人类相互作用组的现状,并为未来应用中选择相互作用组提供了指导。