Truong Cong-Doan, Kwon Yung-Keun
Department of Electrical/Electronic and Computer Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 44610, Republic of Korea.
Faculty of Information Technology, Hanoi Open University, Hanoi, Vietnam.
BMC Syst Biol. 2017 Dec 21;11(Suppl 7):125. doi: 10.1186/s12918-017-0505-2.
Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks.
In this paper, we investigated the changes of modularity and robustness by edge-removal mutations in three signaling networks. We first observed that both the modularity and robustness increased on average in the mutant network by the edge-removal mutations. However, the modularity change was negatively correlated with the robustness change. This implies that it is unlikely that both the modularity and the robustness values simultaneously increase by the edge-removal mutations. Another interesting finding is that the modularity change was positively correlated with the degree, the number of feedback loops, and the edge betweenness of the removed edges whereas the robustness change was negatively correlated with them. We note that these results were consistently observed in randomly structure networks. Additionally, we identified two groups of genes which are incident to the highly-modularity-increasing and the highly-robustness-decreasing edges with respect to the edge-removal mutations, respectively, and observed that they are likely to be central by forming a connected component of a considerably large size. The gene-ontology enrichment of each of these gene groups was significantly different from the rest of genes. Finally, we showed that the highly-robustness-decreasing edges can be promising edgetic drug-targets, which validates the usefulness of our analysis.
Taken together, the analysis of changes of robustness and modularity against edge-removal mutations can be useful to unravel novel dynamical characteristics underlying in signaling networks.
由分子成分和相互作用组成的生物网络由图模型表示。基于该模型已经有一些研究来分析信号网络中结构特征与动态行为之间的关系。然而，对于突变网络中模块性和鲁棒性的变化却很少有人关注。
在本文中，我们通过去除边的突变研究了三个信号网络中模块性和鲁棒性的变化。我们首先观察到，通过去除边的突变，突变网络中的模块性和鲁棒性平均都有所增加。然而，模块性变化与鲁棒性变化呈负相关。这意味着通过去除边的突变不太可能使模块性和鲁棒性值同时增加。另一个有趣的发现是，模块性变化与去除边的度数、反馈环数量和边介数呈正相关，而鲁棒性变化与它们呈负相关。我们注意到这些结果在随机结构网络中也一致观察到。此外，我们分别确定了两组基因，它们分别与去除边的突变导致模块性高度增加和鲁棒性高度降低的边相关联，并观察到它们通过形成一个相当大尺寸的连通分量而可能处于中心位置。这些基因组中每个基因组的基因本体富集与其余基因有显著差异。最后，我们表明高度降低鲁棒性的边可能是有前景的边靶向药物靶点，这验证了我们分析的有用性。
综上所述，针对去除边的突变对鲁棒性和模块性变化的分析有助于揭示信号网络中潜在的新动态特征。
