Evidence map›Paper›PMID 39483422›Full record

ArticleFrontiers in network physiology2024

A statistical analysis method for probability distributions in Erdös-Rényi random networks with preferential cutting-rewiring operation.

Yu Qian, Jiahui Cao, Jing Han, Siyi Zhang, Wentao Chen, Zhao Lei, Xiaohua Cui, Zhigang Zheng

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Article in Frontiers in network physiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Yu QianCollege of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, Baoji, China.
Jiahui CaoCollege of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, Baoji, China.
Jing HanCollege of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, Baoji, China.
Siyi ZhangCollege of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, Baoji, China.
Wentao ChenSchool of Systems Science, Beijing Normal University, Beijing, China.
Zhao LeiCollege of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, Baoji, China.
Xiaohua CuiSchool of Systems Science, Beijing Normal University, Beijing, China.
Zhigang ZhengInstitute of Systems Science, Huaqiao University, Xiamen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study of specific physiological processes from the perspective of network physiology has gained recent attention. Modeling the global information integration among the separated functionalized modules in structural and functional brain networks is a central problem. In this article, the preferentially cutting-rewiring operation (PCRO) is introduced to approximatively describe the above physiological process, which consists of the cutting procedure and the rewiring procedure with specific preferential constraints. By applying the PCRO on the classical Erdös-Rényi random network (ERRN), three types of isolated nodes are generated, based on which the common leaves (CLs) are formed between the two hubs. This makes the initially homogeneous ERRN experience drastic changes and become heterogeneous. Importantly, a statistical analysis method is proposed to theoretically analyze the statistical properties of an ERRN with a PCRO. Specifically, the probability distributions of these three types of isolated nodes are derived, based on which the probability distribution of the CLs can be obtained easily. Furthermore, the validity and universality of our statistical analysis method have been confirmed in numerical experiments. Our contributions may shed light on a new perspective in the interdisciplinary field of complexity science and biological science and would be of great and general interest to network physiology.

Indexed as

biological sciencebrain networkscomplex systemsnetwork modelsnetwork physiology

Identifiers

PMID39483422
PMCPMC11524867

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