Robustness and Evolvability of the Human Signaling Network

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Title: Robustness and Evolvability of the Human Signaling Network
Authors: Kim, Junil
Vandamme, Drieke
Kim, Jeong-Rae
Munoz, Amaya Garcia
Kolch, Walter
Cho, Kwang-Hyun
Permanent link: http://hdl.handle.net/10197/9162
Date: 31-Jul-2014
Abstract: Biological systems are known to be both robust and evolvable to internal and external perturbations, but what causes these apparently contradictory properties? We used Boolean network modeling and attractor landscape analysis to investigate the evolvability and robustness of the human signaling network. Our results show that the human signaling network can be divided into an evolvable core where perturbations change the attractor landscape in state space, and a robust neighbor where perturbations have no effect on the attractor landscape. Using chemical inhibition and overexpression of nodes, we validated that perturbations affect the evolvable core more strongly than the robust neighbor. We also found that the evolvable core has a distinct network structure, which is enriched in feedback loops, and features a higher degree of scale-freeness and longer path lengths connecting the nodes. In addition, the genes with high evolvability scores are associated with evolvability-related properties such as rapid evolvability, low species broadness, and immunity whereas the genes with high robustness scores are associated with robustness-related properties such as slow evolvability, high species broadness, and oncogenes. Intriguingly, US Food and Drug Administration-approved drug targets have high evolvability scores whereas experimental drug targets have high robustness scores.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: Public Library of Science
Copyright (published version): 2014 the Authors
Keywords: Human signaling network;Boolean network modeling;Attractor landscape analysis
DOI: 10.1371/journal.pcbi.1003763
Language: en
Status of Item: Peer reviewed
Appears in Collections:Conway Institute Research Collection
SBI Research Collection
Medicine Research Collection

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