scholarly journals Quantifying the Importance of Firms by Means of Reputation and Network Control

2021 ◽  
Vol 4 ◽  
Author(s):  
Yan Zhang ◽  
Frank Schweitzer
Keyword(s):  
Ownership Structure ◽  
Enrichment Analysis ◽  
Network Control ◽  
Transnational Companies ◽  
Operating Revenue ◽  
Network Controllability

As recently argued in the literature, the reputation of firms can be channeled through their ownership structure. We use this relation to model reputation spillovers between transnational companies and their participated companies in an ownership network core of 1,318 firms. We then apply concepts of network controllability to identify minimum sets of driver nodes (MDSs) of 314 firms in this network. The importance of these driver nodes is classified according to their control contribution, their operating revenue, and their reputation. The latter two are also taken as proxies for the access costs when utilizing firms as driver nodes. Using an enrichment analysis, we find that firms with high reputation maintain the controllability of the network but rarely become top drivers, whereas firms with medium reputation most likely become top driver nodes. We further show that MDSs with lower access costs can be used to control the reputation dynamics in the whole network.

scholarly journals Network controllability in transmodal cortex predicts psychosis spectrum symptoms

2020 ◽  
Author(s):  
Linden Parkes ◽  
Tyler M. Moore ◽  
Monica E. Calkins ◽  
Matthew Cieslak ◽  
David R. Roalf ◽  
...  
Keyword(s):  
Control Theory ◽  
Structural Connectivity ◽  
Prediction Performance ◽  
Network Control ◽  
Association Cortex ◽  
Out Of Sample ◽  
Sample Testing ◽  
Functional Hierarchy ◽  
Structural Connections ◽  
Network Controllability

ABSTRACTBackgroundThe psychosis spectrum is associated with structural dysconnectivity concentrated in transmodal association cortex. However, understanding of this pathophysiology has been limited by an exclusive focus on the direct connections to a region. Using Network Control Theory, we measured variation in both direct and indirect structural connections to a region to gain new insights into the pathophysiology of the psychosis spectrum.MethodsWe used psychosis symptom data and structural connectivity in 1,068 youths aged 8 to 22 years from the Philadelphia Neurodevelopmental Cohort. Applying a Network Control Theory metric called average controllability, we estimated each brain region’s capacity to leverage its direct and indirect structural connections to control linear brain dynamics. Next, using non-linear regression, we determined the accuracy with which average controllability could predict negative and positive psychosis spectrum symptoms in out-of-sample testing. We also compared prediction performance for average controllability versus strength, which indexes only direct connections to a region. Finally, we assessed how the prediction performance for psychosis spectrum symptoms varied over the functional hierarchy spanning unimodal to transmodal cortex.ResultsAverage controllability outperformed strength at predicting positive psychosis spectrum symptoms, demonstrating that indexing indirect structural connections to a region improved prediction performance. Critically, improved prediction was concentrated in association cortex for average controllability, whereas prediction performance for strength was uniform across the cortex, suggesting that indexing indirect connections is crucial in association cortex.ConclusionsExamining inter-individual variation in direct and indirect structural connections to association cortex is crucial for accurate prediction of positive psychosis spectrum symptoms.

scholarly journals The interdependence of corporate reputation and ownership: a network approach to quantify reputation

2019 ◽  
Vol 6 (10) ◽  
pp. 190570 ◽  
Author(s):  
Yan Zhang ◽  
Frank Schweitzer
Keyword(s):  
Ownership Structure ◽  
Corporate Reputation ◽  
Network Approach ◽  
Additional Information ◽  
The Core ◽  
Signalling Theory ◽  
Operating Revenue

We propose a novel way to measure the reputation of firms by using information about their ownership structure. Supported by the signalling theory, we argue that ownership relations channel reputation spillovers between shareholders and their invested companies. We model such reputation spillovers by means of a simple dynamics that runs on the ownership network, constructed from available databases. We focus on the core of the global ownership network with 1300 firms and 12 100 ownership links. Our method assigns an ownership-based reputation value to each firm, used to provide a quantitative reputation ranking. We compare our ranking with alternative rankings, to confirm that the top-ranked firms are correctly identified. We also demonstrate that our reputation measure does not correlate substantially with operating revenue or control and thus provides additional information about firms.

scholarly journals Network controllability enrichment analysis reveals that SARS-CoV-2 infection tends to target indispensable nodes of a directed human protein-protein interaction network

2021 ◽  
Author(s):  
Ho-Joon Lee
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Genome Wide ◽  
A Genome ◽  
Human Proteins ◽  
Protein Protein Interaction Network ◽  
Network Controllability

The COVID-19 disease has been a global threat caused by the new coronavirus species, SARS-CoV-2, since early 2020 with an urgent need for therapeutic interventions. In order to provide insight into human proteins targeted by SARS-CoV-2, here we study a directed human protein-protein interaction network (dhPPIN) based on our previous work on network controllability of virus targets. We previously showed that human proteins targeted by viruses tend to be those whose removal in a dhPPIN requires more control of the network dynamics, which were classified as indispensable nodes. In this study we introduce a more comprehensive rank-based enrichment analysis of our previous dhPPIN for SARS-CoV-2 infection and show that SARS-CoV-2 also tends to target indispensable nodes in the dhPPIN using multiple proteomics datasets, supporting validity and generality of controllability analysis of viral infection in humans. Also, we find differential controllability among SARS-CoV-2, SARS-CoV-1, and MERS-CoV from a comparative proteomics study. Moreover, we show functional significance of indispensable nodes by analyzing heterogeneous datasets from a genome-wide CRISPR screening study, a time-course phosphoproteomics study, and a genome-wide association study. Specifically, we identify SARS-CoV-2 ORF3A as most frequently interacting with indispensable proteins in the dhPPIN, which are enriched in TGF-beta signaling and tend to be sources nodes and interact with each other. Finally, we built an integrated network model of ORF3A-interacting indispensable proteins with multiple functional supports to provide hypotheses for experimental validation as well as therapeutic opportunities. Therefore, a sub-network of indispensable proteins targeted by SARS-CoV-2 could serve as a prioritized network of drug targets and a basis for further functional and mechanistic studies from a network controllability perspective.

scholarly journals Structural controllability predicts functional patterns and brain stimulation benefits associated with working memory

2019 ◽  
Author(s):  
L. Beynel ◽  
L. Deng ◽  
C.A. Crowell ◽  
M. Dannhauer ◽  
H. Palmer ◽  
...  
Keyword(s):  
Working Memory ◽  
Brain Stimulation ◽  
Functional Activity ◽  
Memory Performance ◽  
Network Control ◽  
Global Network ◽  
List Type ◽  
Network Function ◽  
Structural Controllability ◽  
Network Controllability

SummaryThe brain is an inherently dynamic system, and much work has focused on the ability to modify neural activity through both local perturbations and changes in the function of global network ensembles. Network controllability is a recent concept in network science that purports to predict the influence of individual cortical sites on global network states and state changes, thereby creating a unifying account of local influences on global brain dynamics. Here, we present an integrated set of multimodal brain–behavior relationships, acquired from functional magnetic resonance imaging during a transcranial magnetic stimulation intervention, that demonstrate how network controllability influences network function, as well as behavior. This work helps to outline a clear technique for integrating structural network topology and functional activity to predict the influence of a potential stimulation target on subsequent behaviors and prescribes next steps towards predicting neuromodulatory and behavioral responses after brain stimulation.Highlights- This study tested the strength of network controllability using fMRI and rTMS- Controllability correlates with functional modulation of working memory demand load- Controllability is also correlated with the memory improvement from applied rTMS- These findings link network control theory with physiology and behavior.In briefBeynel et al. show that the benefits of functionally targeted brain stimulation on working memory performance can be predicted by network control properties at the stimulated site. Structural controllability and functional activity independently predict this cognitive benefit.Author ContributionsConceptualization & Methodology: L.B, S.W.D., B.L., R.C., L.G.A.; Investigation: L.B., L.D., S.W.D., C.A.C., M.D., H.P., S.H.; Writing—Original Draft: L.B., L.D., S.W.D.; Writing—Review & Editing: L.B., L.D., S.W.D., L.G.A., A.V.P.; Funding Acquisition: S.W.D., R.C., B.L., S.H.L., A.V.P.; Resources: L.G.A., B.L., R.C.; Supervision: L.G.A., S.W.D.

scholarly journals Age-associated network controllability changes in first episode drug-naïve schizophrenia

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Biqiu Tang ◽  
Wenjing Zhang ◽  
Shikuang Deng ◽  
Jiang Liu ◽  
Na Hu ◽  
...  
Keyword(s):  
White Matter ◽  
Control Theory ◽  
Structural Connectivity ◽  
Network Control ◽  
First Episode ◽  
Theory Approach ◽  
Functional Connections ◽  
Age Related ◽  
Drug Naïve ◽  
Network Controllability

Abstract Background Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain’s structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. Methods Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. Results Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. Conclusions By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.

scholarly journals Robustness Analysis of Structural Controllability for Directed Networks Against Single Edge Attacks

2020 ◽  
Vol 9 (8) ◽  
pp. 944-951
Keyword(s):  
Critical Infrastructure ◽  
Dominating Set ◽  
Robustness Analysis ◽  
Network Control ◽  
Single Edge ◽  
Infrastructure Systems ◽  
Malicious Attack ◽  
Graph Classes ◽  
Structural Controllability ◽  
Network Controllability

Infrastructure systems are an essential component, evolving with greater interconnectivity and interdependence at varying degrees. The control robustness of a network against malicious attack and random failure also becomes a further considerable problem in network controllability and its robustness. An adversary who is adequately knowledgeable about the control system can take control of aspects of the network as it can compromise the control network’s subset of critical nodes and/or disconnect parts of the control network resulting in low observability. Therefore, safeguarding critical infrastructure systems from different disruptions is primarily significant. This paper focuses the POWER DOMINATING SET (PDS) problem, originally introduced by Haynes to study the structure of electric power network control systems and their efficient control, as an alternate framework for the examination of the structural controllability of networks. However, PDS is generally known to be NP-complete with low approximability with recent work focusing on studying properties of restricted graph classes. Based on the PDS problem, this paper also is dedicated to studying the different edge attack strategies, as well as the robustness of network controllability of Erd s-Re ́nyi networks with directed control links under single edge attacks. MATLAB will be utilised in order to produce a simulative evaluation for more realistic critical infrastructure networks such as real power networks.

scholarly journals Network controllability: viruses are driver agents in dynamic molecular systems

2018 ◽  
Author(s):  
Vandana Ravindran ◽  
Jose Carlos Nacher ◽  
Tatsuya Akutsu ◽  
Masayuki Ishitsuka ◽  
Adrian Osadcenco ◽  
...  
Keyword(s):  
Control Theory ◽  
Viral Infection ◽  
Dominating Set ◽  
Network Control ◽  
Biological Information ◽  
Maximum Matching ◽  
Effective Control ◽  
Model Control ◽  
Hiv 1 ◽  
Network Controllability

ABSTRACTIn recent years control theory has been applied to biological systems with the aim of identifying the minimum set of molecular interactions that can drive the network to a required state. However in an intra-cellular network it is unclear what ‘control’ means. To address this limitation we use viral infection, specifically HIV-1 and HCV, as a paradigm to model control of an infected cell. Using a large human signalling network comprised of over 6000 human proteins and more than 34000 directed interactions, we compared two dynamic states: normal/uninfected and infected. Our network controllability analysis demonstrates how a virus efficiently brings the dynamic host system into its control by mostly targeting existing critical control nodes, requiring fewer nodes than in the uninfected network. The driver nodes used by the virus are distributed throughout the pathways in specific locations enabling effective control of the cell via the high ‘control centrality’ of the viral and targeted host nodes. Furthermore, this viral infection of the human system permits discrimination between available network-control models, and demonstrates the minimum-dominating set (MDS) method better accounts for how biological information and signals are transferred than the maximum matching (MM) method as it identified most of the HIV-1 proteins as critical driver nodes and goes beyond identifying receptors as the only critical driver nodes. This is because MDS, unlike MM, accounts for the inherent non-linearity of signalling pathways. Our results demonstrate control-theory gives a more complete and dynamic understanding of the viral hijack mechanism when compared with previous analyses limited to static single-state networks.

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