Evidence map›Paper›PMID 29670664›Full record

ArticleComputational and mathematical methods in medicine2018

Novel Model for Cascading Failure Based on Degree Strength and Its Application in Directed Gene Logic Networks.

Yulin Zhang, Maoxian Zhao, Jionglong Su, Xiao Lu, Kebo Lv

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yulin ZhangCollege of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, Shandong, China.
Maoxian ZhaoCollege of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, Shandong, China.ORCID 0000-0001-9310-421X
Jionglong SuDepartment of Mathematical Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China.ORCID 0000-0001-5360-6493
Xiao LuCollege of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, Shandong, China.
Kebo LvSchool of Mathematical Sciences, Ocean University of China, Qingdao 266100, China.ORCID 0000-0001-6539-7844

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel model for cascading failures in a directed logic network based on the degree strength at a node was proposed. The definitions of in-degree and out-degree strength of a node were initially reconsidered, and the load at a nonisolated node was proposed as the ratio of in-degree strength to out-degree strength of the node. The cascading failure model based on degree strength was applied to the logic network for three types of cancer including adenocarcinoma of lung, prostate cancer, and colon cancer based on their gene expression profiles. In order to highlight the differences between the three networks by the cascading failure mechanism, we used the largest-scale cascades and the cumulative cascade probability to depict the damage. It was found that the cascading failures caused by hubs are usually larger. Furthermore, the result shows that propagations against the networks were correlated with the structures motifs of connected logical doublets. Finally, some genes were selected based on cascading failure mechanism. We believe that these genes may be involved in the occurrence and development of three types of cancer.

Indexed as

Gene Regulatory NetworksModels, GeneticAdenocarcinomaAdenocarcinoma of LungColonic NeoplasmsComputational BiologyComputer SimulationDatabases, GeneticFemaleHumansLogistic ModelsLung NeoplasmsMaleModels, StatisticalNeoplasmsProstatic Neoplasms

Identifiers

PMID29670664
PMCPMC5836303

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.