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A metrics method for cellular network structure / 中国组织工程研究
Chinese Journal of Tissue Engineering Research ; (53): 83-86, 2020.
Article in Chinese | WPRIM | ID: wpr-848058
ABSTRACT

BACKGROUND:

Communication between cells is indispensable in a multicellular organism society. Many cells communicate with each other, forming a complex cellular network structure. It is very important to measure and evaluate the relevant attribute values of cellular network structure.

OBJECTIVE:

To propose a metrics method of cellular network structure based on a complex network.

METHODS:

Based on literature research and practical application, the metrics framework of cellular network structure was established. The structure of cellular network was measured in the aspects of the degree of node, the degree distribution of cellular network, the average path length of cellular network and the cluster coefficient of cellular network. A small experiment was taken as an example to verify the validity of the method. RESULTS AND

CONCLUSION:

In the degree distribution of cellular networks, the degree values of most cell nodes are relatively small, and only a small number of cell nodes have higher degree values. The more obvious power-law distribution of the degree distribution P(k) of cell nodes indicates the more reasonable structure of the cellular network as well as the more normal cellular network. At the same time, many cellular network structures have smaller average path lengths. The larger cluster coefficient of the cellular network indicates the higher aggregation characteristics of the cellular network. Generally speaking, the tighter the cell network structure is, the more obvious the clustering characteristics of the cell network structure are, and the more normal the cellular network is.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Tissue Engineering Research Year: 2020 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Tissue Engineering Research Year: 2020 Type: Article