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中心度变异性及其对识别关键基因的影响。

Variability of Betweenness Centrality and Its Effect on Identifying Essential Genes.

机构信息

Math Department, Claremont Graduate University, Claremont, CA, 91711, USA.

Neurology and Neurological Sciences, Stanford University Medical Center, Palo Alto, CA, USA.

出版信息

Bull Math Biol. 2019 Sep;81(9):3655-3673. doi: 10.1007/s11538-018-0526-z. Epub 2018 Oct 22.

DOI:10.1007/s11538-018-0526-z
PMID:30350013
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6476710/
Abstract

This paper begins to build a theoretical framework that would enable the pharmaceutical industry to use network complexity measures as a way to identify drug targets. The variability of a betweenness measure for a network node is examined through different methods of network perturbation. Our results indicate a robustness of betweenness centrality in the identification of target genes.

摘要

本文旨在构建一个理论框架，使制药行业能够将网络复杂性度量作为一种识别药物靶点的方法。通过不同的网络扰动方法来检验网络节点介数的可变性。研究结果表明，介数中心度在识别靶基因方面具有稳健性。

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本文引用的文献

[1]
Graph complexity analysis identifies an ETV5 tumor-specific network in human and murine low-grade glioma.

PLoS One. 2018-5-22

[2]
DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

PLoS One. 2017-11-9

[3]
SOX8 regulates cancer stem-like properties and cisplatin-induced EMT in tongue squamous cell carcinoma by acting on the Wnt/β-catenin pathway.

Int J Cancer. 2017-11-6

[4]
Transglutaminase 2 Inhibition Reverses Mesenchymal Transdifferentiation of Glioma Stem Cells by Regulating C/EBPβ Signaling.

Cancer Res. 2017-7-28

[5]
Ccl5 establishes an autocrine high-grade glioma growth regulatory circuit critical for mesenchymal glioblastoma survival.

Oncotarget. 2017-5-16

[6]
Estimating psychological networks and their accuracy: A tutorial paper.

Behav Res Methods. 2018-2

[7]
Olig1 is required for noggin-induced neonatal myelin repair.

Ann Neurol. 2017-4

[8]
EGFR and C/EBP-β oncogenic signaling is bidirectional in human glioma and varies with the C/EBP-β isoform.

FASEB J. 2016-12

[9]
Network topology measures for identifying disease-gene association in breast cancer.

BMC Bioinformatics. 2016-7-25

[10]
ARACNe-AP: gene network reverse engineering through adaptive partitioning inference of mutual information.

Bioinformatics. 2016-7-15

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