scholarly journals An Analysis of Eccentricity-Based Invariants for Biochemical Hypernetworks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Muhammad Aamer Rashid ◽  
Sarfraz Ahmad ◽  
Muhammad Kamran Siddiqui ◽  
Shazia Manzoor ◽  
Mlamuli Dhlamini
Keyword(s):  
Infectious Diseases ◽  
Communication Networks ◽  
Biological Networks ◽  
Biochemical Networks ◽  
Theoretical Frameworks ◽  
Information Theoretic ◽  
Corona Product

Biological proceedings are well characterized by solid illustrations for communication networks. The framework of biological networks has to be considered together with the expansion of infectious diseases like coronavirus. Also, the graph entropies have established themselves as the information theoretic measure to evaluate the architectural information of biological networks. In this article, we examined conclusive biochemical networks like t -level hypertrees along with the corona product of hypertrees with path. We computed eccentricity-based indices for the depiction of aforementioned theoretical frameworks of biochemical networks. Furthermore, explicit depiction of the graph entropies with these indices is also measured.

Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey

2022 ◽  
Vol 54 (8) ◽  
pp. 1-36
Author(s):  
Satyaki Roy ◽  
Preetam Ghosh ◽  
Nirnay Ghosh ◽  
Sajal K. Das
Keyword(s):  
Communication Networks ◽  
Biological Networks ◽  
Regulatory Network ◽  
Large Scale ◽  
Data Transfer ◽  
Transcriptional Regulatory Network ◽  
Future Research ◽  
Transcriptional Regulatory ◽  
Iot Devices ◽  
Networking Protocols

The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment—the very optimization challenges that are dealt with by biological networks as a consequence of millions of years of evolution. The transcriptional regulatory network (TRN) is a biological network whose innate topological robustness is a function of its underlying graph topology. In this article, we survey these properties of TRN and the metrics derived therefrom that lend themselves to the design of smart networking protocols and architectures. We then review a body of literature on bio-inspired networking solutions that leverage the stated properties of TRN. Finally, we present a vision for specific aspects of TRNs that may inspire future research directions in the fields of large-scale social and communication networks.

Graph Mining Techniques

2013 ◽  
pp. 446-464 ◽  
Author(s):  
Ana Paula Appel ◽  
Christos Faloutsos ◽  
Caetano Traina Junior
Keyword(s):  
Social Networks ◽  
Communication Networks ◽  
Real World ◽  
Biological Networks ◽  
Graph Mining ◽  
Recommendation Systems ◽  
Computer Communication Networks ◽  
Computer Communication ◽  
Good Pattern ◽  
As Graph

Graphs appear in several settings, like social networks, recommendation systems, computer communication networks, gene/protein biological networks, among others. A large amount of graph patterns, as well as graph generator models that mimic such patterns have been proposed over the last years. However, a deep and recurring question still remains: “What is a good pattern?” The answer is related to finding a pattern or a tool able to help distinguishing between actual real-world and fake graphs. Here we explore the ability of ShatterPlots, a simple and powerful algorithm to tease out patterns of real graphs, helping us to spot fake/masked graphs. The idea is to force a graph to reach a critical (“Shattering”) point, randomly deleting edges, and study its properties at that point.

scholarly journals Which measures matter? A behavioral ecology view of “market integration” among the matrilineal Mosuo of Southwest China

2021 ◽  
Author(s):  
Siobhan Mattison ◽  
Darragh Hare ◽  
Adam Z. Reynolds ◽  
Chun-Yi Sum ◽  
Mary K Shenk ◽  
...  
Keyword(s):  
Decision Making ◽  
Social Organization ◽  
Behavioral Ecology ◽  
Market Integration ◽  
Southwest China ◽  
Theoretic Model ◽  
Theoretical Frameworks ◽  
Information Theoretic ◽  
Reproductive Decision Making ◽  
Individual Household

Market integration (MI) is a complex process through which individuals transition from relatively subsistence-based to market-oriented activities. Changes associated with MI alter the landscapes of individual health and reproductive decision-making. While the consequences of MI are often easily detected, the specific pathways through which MI affects decision-making are context-dependent and under-investigated. We employed an information-theoretic model selection approach to characterize relationships between multiple indicators of MI and three outcomes commonly associated with MI, waist circumference (n = 431), systolic blood pressure (n = 472), and age at first reproduction (n = 974), among adult matrilineal Mosuo participants from 505 households in six villages in southwest China. Different MI indicators, distributed across individual, household, and community levels of social organization, predicted these three outcomes, demonstrating that individuals’ personal circumstances, household structure, and community affect how they experience and respond to MI. We emphasize the importance of identifying and measuring multiple context-appropriate indicators of MI across levels of social organization. Theoretical frameworks that situate hypotheses of MI within specific social, cultural, and historical contexts will be most capable of identifying specific pathways through which multiple elements of MI affect different domains of decision making.

Physical Layer Security and Its Applications

2014 ◽  
pp. 29-60
Author(s):  
Rajesh K. Sharma
Keyword(s):  
Communication Networks ◽  
Physical Layer Security ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Physical Layer ◽  
Key Generation ◽  
Information Theoretic ◽  
Communication Devices ◽  
Input Multiple Output ◽  
Multiple Relay

This chapter provides a survey of physical layer security and key generation methods. This includes mainly an overview of ongoing research in physical layer security in the present and next generation communication networks. Although higher layer security mechanisms and protocols address wireless security challenges in large extent, more security vulnerabilities arise due to the increasingly pervasive existence of wireless communication devices. In this context, the focus of this chapter is mainly on physical layer security. Some security attacks in general are briefly reviewed. Models of physical layer security, information theoretic works, and key generation methods including quantization and reconciliation are discussed. Some latest developments for enhanced security like Multiple-Input Multiple-Output (MIMO) systems, reconfigurable antennas, and multiple relay systems are also presented. Finally, some existing and emerging application scenarios of physical layer security are discussed.

Time Complexity Analyses on Fast Grid Layout Algorithm

2012 ◽  
Vol 442 ◽  
pp. 436-440
Author(s):  
Sheng He ◽  
Yu Pan ◽  
Quan Fa Zhou ◽  
Bing Zhou ◽  
Dan Chen ◽  
...  
Keyword(s):  
Biological Networks ◽  
Time Complexity ◽  
Biochemical Networks ◽  
Layout Algorithm ◽  
Highly Efficient ◽  
Original Grid ◽  
Grid Layout

To analyze and visualize biological networks are hot in bioinformatics. Fast grid layout is a new highly efficient visualization algorithm that has advantages in generating compact layouts with biologically comprehensible modules of biochemical networks. The time complexity analyses are very important to visualization algorithm research. In this paper, we estimated analytically the time complexity of fast grid layout in detail. Experiment results for biological networks of different sizes testified the estimate. Compared with original grid layout, we also discussed the main reasons of ensuring good performance of fast grid layout.

scholarly journals Topological properties of robust biological and computational networks

2014 ◽  
Vol 11 (96) ◽  
pp. 20140283 ◽  
Author(s):  
Saket Navlakha ◽  
Xin He ◽  
Christos Faloutsos ◽  
Ziv Bar-Joseph
Keyword(s):  
Communication Networks ◽  
Biological Networks ◽  
Environmental Variability ◽  
Joint Analysis ◽  
Topological Properties ◽  
Global Networks ◽  
Important Principle ◽  
Simple Change ◽  
The Rich ◽  
Novel Algorithms

Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields.

scholarly journals An Algorithm based on Heap of Binary Search Tree to Solve Graph Coloring Problem

2019 ◽  
Vol 8 (2) ◽  
pp. 3920-3924
Keyword(s):  
Communication Networks ◽  
Graph Coloring ◽  
Biological Networks ◽  
Hybrid Approach ◽  
Search Tree ◽  
Binary Search ◽  
Binary Search Tree ◽  
Coloring Problem ◽  
Graph Coloring Problem ◽  
The Given

Graph coloring problem is one of most frequent studied problem in the graph theory due to its uses in different area of applications like simulation of biological networks, communication networks, register allocation and many more. This problem involves the coloring of the vertices of the given a graph G (V, E) with number of available colors in such a manner that adjacent vertices must assign colors different with each other. In this paper we present a hybrid approach to assign the colors to vertices of the given graph that is based on adjacency matrix and search tree data structure. The coloring process for a particular vertex in the graph will done by getting the feasible colors available in the color list. The feasible colors that may be assigned to a vertex, retrieved from the vertex-color binary search tree generated initially for available colors. The proposed solution for the graph coloring problem is efficient in terms of its running time complexity and it will work without affecting its complexity for any kind of graph.

scholarly journals Conspiracy Theories about Infectious Diseases: An Introduction

2021 ◽  
Vol 15 ◽  
pp. 183449092110576
Author(s):  
Ying-yi Hong ◽  
Hoi-Wing Chan ◽  
Karen M. Douglas
Keyword(s):  
Infectious Diseases ◽  
Disease Outbreaks ◽  
Social Needs ◽  
Theoretical Frameworks ◽  
Future Directions ◽  
Conspiracy Theories ◽  
Conspiracy Beliefs ◽  
Antecedents And Consequences ◽  
Consequences Of Disease ◽  
Shed Light

Understanding why people believe conspiracy theories related to disease outbreaks and the consequences of such beliefs is critical for combating both the COVID-19 pandemic and its corresponding “infodemic.” In the introduction to this special issue on conspiracy theories about infectious diseases, the authors first provide a brief overview of the narratives of conspiracy theories related to COVID-19, followed by a review of extant theoretical frameworks regarding the psychology of conspiracy beliefs. Specifically, they discuss how epistemic, existential, and social needs contribute to the holding of conspiracy beliefs. Then, the authors summarize the major findings from the nine empirical articles featured in this issue, particularly how they shed light on the antecedents and consequences of disease-related conspiracy beliefs. They conclude by discussing future directions for the study of disease-related conspiracy beliefs.

scholarly journals Using biological networks to improve our understanding of infectious diseases

2014 ◽  
Vol 11 (18) ◽  
pp. 1-10 ◽  
Author(s):  
Nicola J. Mulder ◽  
Richard O. Akinola ◽  
Gaston K. Mazandu ◽  
Holifidy Rapanoel
Keyword(s):  
Infectious Diseases ◽  
Biological Networks

scholarly journals Biological networks with singular Jacobians: their origins and adaptation criteria

2021 ◽  
Author(s):  
Tracey Oellerich ◽  
Maria Emelianenko ◽  
Lance Liotta ◽  
Robyn P. Araujo
Keyword(s):  
Conservation Laws ◽  
Biological Networks ◽  
Complex Dynamics ◽  
Singular Systems ◽  
Multiple Input Multiple Output ◽  
Mass Action ◽  
System Response ◽  
Theoretical Frameworks ◽  
Single Input Single Output ◽  
Nonlinear Conservation Laws

ABSTRACTThis work is focused on Ordinary Differential Equations(ODE)-based models of biochemical systems that possess a singular Jacobian manifesting in non-hyperbolic equilibria. We show that there are several classes of systems that exhibit this behavior: a)systems with monomial-type interaction terms and b)systems with linear or nonlinear conservation laws. While models derived from mass-action principles often present with linear conservation laws stemming from the underlying biologic rationale, nonlinear conservation laws are more subtle and harder to detect. Nevertheless, in both situations the corresponding ODE system will contain non-hyperbolic equilibria. While having a potentially more complex dynamics and falling outside of the scope of existing theoretical frameworks, this class of systems can still exhibit adapting behavior associated with certain nodes and inputs. We derive a generalized adaptation condition that extends to singular systems and is compatible with both single-input/single-output and multiple-input/multiple-output settings. The approach explored herein, based on the notion of Moore-Penrose pseudoinverse, is tested on several synthetic systems that are shown to exhibit homeostatic behavior but are not covered by existing methods. These results highlight the role of the network structure and modeling assumptions when understanding system response to input and can be helpful in discovering intrinsic relationships between the nodes.

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