Modularity

Summary

Broadly speaking, modularity is the degree to which a system's components may be separated and recombined, often with the benefit of flexibility and variety in use. The concept of modularity is used primarily to reduce complexity by breaking a system into varying degrees of interdependence and independence across and "hide the complexity of each part behind an abstraction and interface". However, the concept of modularity can be extended to multiple disciplines, each with their own nuances. Despite these nuances, consistent themes concerning modular systems can be identified. Contextual nuances The meaning of the word "modularity" can vary somewhat based on context. The following are contextual examples of modularity across several fields of science, technology, industry, and culture: Science *In biology, modularity recognizes that organisms or metabolic pathways are composed of modules. *In ecology, modularity is considered a key factor—along with diversity and f

Official source

https://en.wikipedia.org/wiki/Modularity

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Related publications (100)

NEMo: An Evolutionary Model with Modularity for PPI Networks

Qijia Jiang, Bernard Moret, Gabriela Clara Racz, Min Ye, Xiuwei Zhang

Modelling the evolution of biological networks is a major challenge. Biological networks are usually represented as graphs; evolutionary events include addition and removal of vertices and edges, but also duplication of vertices and their associated edges. Since duplication is viewed as a primary driver of genomic evolution, recent work has focused on duplication-based models. Missing from these models is any embodiment of modularity, a widely accepted attribute of biological networks. Some models spontaneously generate modular structures, but none is known to maintain and evolve them. We describe NEMo (Network Evolution with Modularity), a new model that embodies modularity. NEMo allows modules to emerge and vanish, to fission and merge, all driven by the underlying edge-level events using a duplication-based process. We introduce measures to compare biological networks in terms of their modular structure and use them to compare NEMo and existing duplication-based models and to compare both generated and published networks.

Springer Int Publishing Ag2016

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Modeling the evolution of biological networks is a major challenge. Biological networks are usually represented as graphs; evolutionary events not only include addition and removal of vertices and edges but also duplication of vertices and their associated edges. Since duplication is viewed as a primary driver of genomic evolution, recent work has focused on duplication-based models. Missing from these models is any embodiment of modularity, a widely accepted attribute of biological networks. Some models spontaneously generate modular structures, but none is known to maintain and evolve them. We describe network evolution with modularity (NEMo), a new model that embodies modularity. NEMo allows modules to appear and disappear and to fission and to merge, all driven by the underlying edge-level events using a duplication-based process. We also introduce measures to compare biological networks in terms of their modular structure; we present comparisons between NEMo and existing duplication-based models and run our measuring tools on both generated and published networks. Index indicates

IEEE Press2017

3PAC: A Plug-and-Play System for Distributed Power Sharing and Communication in Modular Robots

Christoph Heinrich Belke, Kevin Andrew Holdcroft, Jamie Paik

In modular robotics, there is classically a compromise between coupling complexity and functionality. The mechanical and electrical designs are linked, such that adding electrical features often requires redesigning the mechanical components. However, increasing the functionality of each electrical contact adds capabilities or redundancies to existing robots without redesigning the coupling and allows for fewer contacts in new designs. This article presents a power distribution and local communication system for modular robotics, using only three electrical contacts between modules. The proposed system can be easily recreated, modeled, and outfitted into an existing modular robotic coupling to introduce power sharing, communication, or redundancy, without increasing the couplings mechanical complexity. By focusing on local power transfer, the system is scalable in number as well as coherent with modularity. We demonstrate that, through this system, distributed power sharing can improve the runtime of a simple modular robotic system by up to 62% while maintaining local communication streams. The circuit is modeled through empirical characteristics and therefore the same methods can predict the power distribution accurately in any other modular robot.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

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