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Properties of Boolean dynamics by node classification using feedback loops in a network

Overview of attention for article published in BMC Systems Biology, August 2016
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Title
Properties of Boolean dynamics by node classification using feedback loops in a network
Published in
BMC Systems Biology, August 2016
DOI 10.1186/s12918-016-0322-z
Pubmed ID
Authors

Yung-Keun Kwon

Abstract

Biological networks keep their functions robust against perturbations. Many previous studies through simulations or experiments have shown that feedback loop (FBL) structures play an important role in controlling the network robustness without fully explaining how they do it. Hence, there is a pressing need to more rigorously analyze the influence of FBL structures on network robustness. In this paper, I propose a novel node classification notion based on the FBL structures involved. More specifically, I classify a node as a no-FBL-in-upstream (NFU) or no-FBL-in-downstream (NFD) node if no feedback loop is involved with any upstream or downstream path of the node, respectively. Based on those definitions, I first prove that every NFU node is eventually frozen in Boolean dynamics. Thus, NFU nodes converge to a fixed value determined by the upstream source nodes. Second, I prove that a network is robust against an arbitrary state perturbation subject to a non-source NFD node. This implies that a network state eventually sustains the attractor despite a perturbation subject to a non-source NFD node. Inspired by this result, I further propose a perturbation-sustainable probability that indicates how likely a perturbation effect is to be sustained through propagations. I show that genes with a high perturbation-sustainable probability are likely to be essential, disease, and drug-target genes in large human signaling networks. Taken together, these results will promote understanding of the effects of FBL on network robustness in a more rigorous manner.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 44%
Student > Ph. D. Student 2 22%
Researcher 1 11%
Student > Master 1 11%
Unknown 1 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 44%
Biochemistry, Genetics and Molecular Biology 2 22%
Social Sciences 1 11%
Unknown 2 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 August 2016.
All research outputs
#7,162,789
of 8,282,830 outputs
Outputs from BMC Systems Biology
#756
of 850 outputs
Outputs of similar age
#212,901
of 252,871 outputs
Outputs of similar age from BMC Systems Biology
#33
of 39 outputs
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