Degree-preserving network growth

AbstractBrain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs.

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Likelihood-based approach to discriminate mixtures of network models that vary in time

Scientific Reports ◽

10.1038/s41598-021-84085-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Naomi A. Arnold ◽

Raul J. Mondragón ◽

Richard G. Clegg

Keyword(s):

Network Model ◽

Change Point ◽

Network Science ◽

Preferential Attachment ◽

Network Models ◽

Explanatory Models ◽

Growth Mechanisms ◽

Artificial Data ◽

Network Growth ◽

Over Time

AbstractDiscriminating between competing explanatory models as to which is more likely responsible for the growth of a network is a problem of fundamental importance for network science. The rules governing this growth are attributed to mechanisms such as preferential attachment and triangle closure, with a wealth of explanatory models based on these. These models are deliberately simple, commonly with the network growing according to a constant mechanism for its lifetime, to allow for analytical results. We use a likelihood-based framework on artificial data where the network model changes at a known point in time and demonstrate that we can recover the change point from analysis of the network. We then use real datasets and demonstrate how our framework can show the changing importance of network growth mechanisms over time.

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A novel role for WAVE1 in controlling actin network growth rate and architecture

Molecular Biology of the Cell ◽

10.1091/mbc.e14-10-1477 ◽

2015 ◽

Vol 26 (3) ◽

pp. 495-505 ◽

Cited By ~ 9

Author(s):

Meredith O. Sweeney ◽

Agnieszka Collins ◽

Shae B. Padrick ◽

Bruce L. Goode

Keyword(s):

Actin Filament ◽

Specific Activity ◽

Inhibitory Effect ◽

Actin Network ◽

Inhibitory Effects ◽

Cellular Functions ◽

Network Growth ◽

Assembly Kinetics ◽

Filament Networks ◽

First Time

Branched actin filament networks in cells are assembled through the combined activities of Arp2/3 complex and different WASP/WAVE proteins. Here we used TIRF and electron microscopy to directly compare for the first time the assembly kinetics and architectures of actin filament networks produced by Arp2/3 complex and dimerized VCA regions of WAVE1, WAVE2, or N-WASP. WAVE1 produced strikingly different networks from WAVE2 or N-WASP, which comprised unexpectedly short filaments. Further analysis showed that the WAVE1-specific activity stemmed from an inhibitory effect on filament elongation both in the presence and absence of Arp2/3 complex, which was observed even at low stoichiometries of WAVE1 to actin monomers, precluding an effect from monomer sequestration. Using a series of VCA chimeras, we mapped the elongation inhibitory effects of WAVE1 to its WH2 (“V”) domain. Further, mutating a single conserved lysine residue potently disrupted WAVE1's inhibitory effects. Taken together, our results show that WAVE1 has unique activities independent of Arp2/3 complex that can govern both the growth rates and architectures of actin filament networks. Such activities may underlie previously observed differences between the cellular functions of WAVE1 and WAVE2.

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A phenomenological density-scaling approach to lamellipodial actin dynamics

Interface Focus ◽

10.1098/rsfs.2014.0006 ◽

2014 ◽

Vol 4 (6) ◽

pp. 20140006 ◽

Cited By ~ 11

Author(s):

Alexandre Lewalle ◽

Marco Fritzsche ◽

Kerry Wilson ◽

Richard Thorogate ◽

Tom Duke ◽

...

Keyword(s):

Protein Function ◽

Cell Types ◽

Actin Dynamics ◽

Theoretical Modelling ◽

Network Growth ◽

Genetic Intervention ◽

Regulatory Processes ◽

Observable Behaviour ◽

Different Cell Types

The integration of protein function studied in vitro in a dynamic system like the cell lamellipodium remains a significant challenge. One reason is the apparent contradictory effect that perturbations of some proteins can have on the overall lamellipodium dynamics, depending on exact conditions. Theoretical modelling offers one approach for understanding the balance between the mechanisms that drive and regulate actin network growth and decay. Most models use a ‘bottom-up’ approach, involving explicitly assembling biochemical components to simulate observable behaviour. Their correctness therefore relies on both the accurate characterization of all the components and the completeness of the relevant processes involved. To avoid potential pitfalls due to this uncertainty, we used an alternative ‘top-down’ approach, in which measurable features of lamellipodium behaviour, here observed in two different cell types (HL60 and B16-F1), directly inform the development of a simple phenomenological model of lamellipodium dynamics. We show that the kinetics of F-actin association and dissociation scales with the local F-actin density, with no explicit location dependence. This justifies the use of a simplified kinetic model of lamellipodium dynamics that yields predictions testable by pharmacological or genetic intervention. A length-scale parameter (the lamellipodium width) emerges from this analysis as an experimentally accessible probe of network regulatory processes.

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Embedded Nanowire Network Growth and Node Device Fabrication for GaAs-Based High-Density Hexagonal Binary Decision Diagram Quantum Circuits

Japanese Journal of Applied Physics ◽

10.1143/jjap.45.3614 ◽

2006 ◽

Vol 45 (4B) ◽

pp. 3614-3620 ◽

Cited By ~ 2

Author(s):

Takahiro Tamura ◽

Isao Tamai ◽

Seiya Kasai ◽

Taketomo Sato ◽

Hideki Hasegawa ◽

...

Keyword(s):

Binary Decision Diagram ◽

Device Fabrication ◽

High Density ◽

Quantum Circuits ◽

Network Growth ◽

Binary Decision ◽

Nanowire Network

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Firm’s strategic choices and network knowledge dynamics: how do they affect innovation?

Journal of Knowledge Management ◽

10.1108/jkm-12-2016-0524 ◽

2018 ◽

Vol 22 (1) ◽

pp. 1-20 ◽

Cited By ~ 11

Author(s):

Jose Antonio Belso-Martinez ◽

Isabel Diez-Vial

Keyword(s):

Absorptive Capacity ◽

Knowledge Networks ◽

Knowledge Network ◽

Strategic Choices ◽

Network Growth ◽

Content Type ◽

Endogenous Factors ◽

The Impact ◽

Innovative Capacity ◽

Over Time

Purpose This paper aims to explain how the evolution of knowledge networks and firms’ strategic choices affect innovation. Endogenous factors associated with a path-dependent evolution of the knowledge network are jointly considered with a firm’s development of international relationships and increasing internal absorptive capacity over time. Design/methodology/approach In a biotech cluster, the authors gathered data on the firms’ characteristics and network relationships by asking about the technological knowledge they received in the cluster in 2007 and 2012 – “roster-recall” method. Estimation results were obtained using moderated regression analysis. Findings Firms that increase their involvement in knowledge networks over time also tend to increase their innovative capacity. However, efforts devoted to building international links or absorptive capacity negatively moderate the impact of network growth on innovation. Practical implications Practitioners have two alternative ways of increasing innovation inside knowledge networks: they can increase their centrality by developing their knowledge network interactions or invest in developing their internal absorptive capacity and new international sources of knowledge. Investing in both of these simultaneously does not seem to improve a firm’s innovative capacity. Originality/value Coupling firms’ strategic options with knowledge network dynamics provide a more complete way of explaining how firms can improve their innovative capacity.

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