Assessing the impact of network depth on the analysis of PPI networks: A case study

机译：评估网络深度对PPI网络分析的影响：一个案例研究

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Recent years have seen a growing interest in the incorporation of protein-protein interaction (PPI) networks to support functional genomic research. Often a default depth is assumed by network inference software. This case study considers the impact of network depth on the analysis of PPI networks using seven proteins known to be relevant to heart failure as inputs into the analysis. This paper analyses how the characteristics of a PPI network vary according to the level examined, suggesting that the investigation of network topology is an essential first step in PPI analysis. The classification of nodes, in terms of degree and betweenness centrality, within the network is also considered. The effect of network depth is also proved to be significant in the identification of potentially essential proteins with large connectivity and/or high betweenness centrality values.

机译：近年来，人们越来越关注将蛋白质-蛋白质相互作用（PPI）网络纳入支持功能基因组研究的兴趣。网络推断软件通常会采用默认深度。本案例研究考虑了使用7种已知与心力衰竭相关的蛋白质作为分析输入时，网络深度对PPI网络分析的影响。本文分析了PPI网络的特性如何根据所检查的级别而变化，这表明对网络拓扑的研究是PPI分析中必不可少的第一步。还考虑了网络内节点的分类（根据程度和中间性）。网络深度的影响也被证明在鉴定具有大连通性和/或高中间性中心值的潜在必需蛋白质方面很重要。

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《Computational Intelligence in Bioinformatics and Computational Biology, 2009. CIBCB '09》|2009年|200-207|共8页
会议地点 Nashville TN(US);Nashville TN(US)
作者
Blayney J.K.; Haiying Wang; Huiru Zheng; Azuaje F.;
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Fac. of Comput. Eng., Univ. of Ulster, Newtownabbey;

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biocybernetics; cardiology; cellular biophysics; genomics; molecular biophysics; network theory (graphs); proteins; PPI network analysis; betweenness centrality value; connectivity value; functional genomic research; heart failure relevant proteins; network depth effects; network inference software; network node classification; network topology; protein-protein interaction networks;

机译：生物周期论;心脏病学;细胞生物物理学;基因组学;分子生物物理学;网络理论（图）;蛋白质; PPI网络分析;中间性中心值;连通性值;功能基因组研究;与心力衰竭有关的蛋白质;网络深度效应;网络推断软件;网络节点分类；网络拓扑；蛋白质-蛋白质相互作用网络;

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Assessing the impact of network depth on the analysis of PPI networks: A case study

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