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Open AccessJournal ArticleDOI

Community detection in networks: A user guide

TLDR
In this paper, the authors present a guided tour of the main aspects of community detection in networks and point out strengths and weaknesses of popular methods, and give directions to their use.
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This article is published in Physics Reports.The article was published on 2016-11-11 and is currently open access. It has received 1398 citations till now. The article focuses on the topics: Network science & Strengths and weaknesses.

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A connectome and analysis of the adult Drosophila central brain

Louis K. Scheffer, +114 more
- 07 Sep 2020 - 
TL;DR: Improved methods are summarized and the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster is presented, reducing the effort needed to answer circuit questions and providing procedures linking the neurons defined by the analysis with genetic reagents.
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Random walks and diffusion on networks

TL;DR: The theory and applications of random walks on networks are surveyed, restricting ourselves to simple cases of single and non-adaptive random walkers, and three main types are distinguished: discrete-time random walks, node-centric continuous-timerandom walks, and edge-centric Continuous-Time random walks.
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The multilayer nature of ecological networks.

TL;DR: In this article, the authors formally define ecological multilayer networks based on a review of previous, related approaches; illustrate their application and potential with analyses of existing data; and discuss limitations, challenges, and future applications.
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Random walks and diffusion on networks

TL;DR: Random walks have been studied for many decades on both regular lattices and (especially in the last couple of decades) on networks with a variety of structures as discussed by the authors, and they are one of the most fundamental types of stochastic processes; can be used to model numerous phenomena, including diffusion, interactions, and opinions among humans and animals; and can extract information about important entities or dense groups of entities in networks.
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Origins and Evolution of the Global RNA Virome.

TL;DR: A detailed phylogenomic reconstruction of the evolution of the dramatically expanded global RNA virome reveals the relationships between different Baltimore classes of viruses and indicates extensive transfer of viruses between distantly related hosts, such as plants and animals.
References
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Some methods for classification and analysis of multivariate observations

TL;DR: The k-means algorithm as mentioned in this paper partitions an N-dimensional population into k sets on the basis of a sample, which is a generalization of the ordinary sample mean, and it is shown to give partitions which are reasonably efficient in the sense of within-class variance.
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The anatomy of a large-scale hypertextual Web search engine

TL;DR: This paper provides an in-depth description of Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and looks at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.
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Community structure in social and biological networks

TL;DR: This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.
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Data clustering: a review

TL;DR: An overview of pattern clustering methods from a statistical pattern recognition perspective is presented, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners.
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Finding and evaluating community structure in networks.

TL;DR: It is demonstrated that the algorithms proposed are highly effective at discovering community structure in both computer-generated and real-world network data, and can be used to shed light on the sometimes dauntingly complex structure of networked systems.
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