An Empirical Study of Immune System Based On Bipartite Network

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Zou, Sheng-Rong
Peng, Yu-Jing
Guo, Zhong-Wei
Zhou, Ta
Gu, Chang-gui
He, Da-Ren
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Abstract
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Immune system is the most important defense system to resist human pathogens. In this paper we present an immune model with bipartite graphs theory. We collect data through COPE database and construct an immune cell- mediators network. The act degree distribution of this network is proved to be power-law, with index of 1.8. From our analysis, we found that some mediators with high degree are very important mediators in the process of regulating immune activity, such as TNF-alpha, IL-8, TNF-alpha receptors, CCL5, IL-6, IL-2 receptors, TNF-beta receptors, TNF-beta, IL-4 receptors, IL-1 beta, CD54 and so on. These mediators are important in immune system to regulate their activity. We also found that the assortative of the immune system is -0.27. It reveals that our immune system is non-social network. Finally we found similarity of the network is 0.13. Each two cells are similar to small extent. It reveals that many cells have its unique features. The results show that this model could describe the immune system comprehensive.
Comment: 6 pages, 5 figures
Keywords
Nonlinear Sciences - Adaptation and Self-Organizing Systems, Quantitative Biology - Cell Behavior
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