Literature DB >> 25679659

Estimating the resolution limit of the map equation in community detection.

Tatsuro Kawamoto1, Martin Rosvall2.   

Abstract

A community detection algorithm is considered to have a resolution limit if the scale of the smallest modules that can be resolved depends on the size of the analyzed subnetwork. The resolution limit is known to prevent some community detection algorithms from accurately identifying the modular structure of a network. In fact, any global objective function for measuring the quality of a two-level assignment of nodes into modules must have some sort of resolution limit or an external resolution parameter. However, it is yet unknown how the resolution limit affects the so-called map equation, which is known to be an efficient objective function for community detection. We derive an analytical estimate and conclude that the resolution limit of the map equation is set by the total number of links between modules instead of the total number of links in the full network as for modularity. This mechanism makes the resolution limit much less restrictive for the map equation than for modularity; in practice, it is orders of magnitudes smaller. Furthermore, we argue that the effect of the resolution limit often results from shoehorning multilevel modular structures into two-level descriptions. As we show, the hierarchical map equation effectively eliminates the resolution limit for networks with nested multilevel modular structures.

Year:  2015        PMID: 25679659     DOI: 10.1103/PhysRevE.91.012809

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  11 in total

1.  A Shadowing Problem in the Detection of Overlapping Communities: Lifting the Resolution Limit through a Cascading Procedure.

Authors:  Jean-Gabriel Young; Antoine Allard; Laurent Hébert-Dufresne; Louis J Dubé
Journal:  PLoS One       Date:  2015-10-13       Impact factor: 3.240

2.  Graph Analysis and Modularity of Brain Functional Connectivity Networks: Searching for the Optimal Threshold.

Authors:  Cécile Bordier; Carlo Nicolini; Angelo Bifone
Journal:  Front Neurosci       Date:  2017-08-03       Impact factor: 4.677

3.  Community detection in weighted brain connectivity networks beyond the resolution limit.

Authors:  Carlo Nicolini; Cécile Bordier; Angelo Bifone
Journal:  Neuroimage       Date:  2016-11-16       Impact factor: 6.556

4.  Hierarchical communities in the walnut structure of the Japanese production network.

Authors:  Abhijit Chakraborty; Yuichi Kichikawa; Takashi Iino; Hiroshi Iyetomi; Hiroyasu Inoue; Yoshi Fujiwara; Hideaki Aoyama
Journal:  PLoS One       Date:  2018-08-29       Impact factor: 3.240

5.  Increasing trend of scientists to switch between topics.

Authors:  An Zeng; Zhesi Shen; Jianlin Zhou; Ying Fan; Zengru Di; Yougui Wang; H Eugene Stanley; Shlomo Havlin
Journal:  Nat Commun       Date:  2019-07-31       Impact factor: 14.919

Review 6.  Integrated Computational Approaches and Tools forAllosteric Drug Discovery.

Authors:  Olivier Sheik Amamuddy; Wayde Veldman; Colleen Manyumwa; Afrah Khairallah; Steve Agajanian; Odeyemi Oluyemi; Gennady Verkhivker; Ozlem Tastan Bishop
Journal:  Int J Mol Sci       Date:  2020-01-28       Impact factor: 5.923

7.  Modular structure of brain functional networks: breaking the resolution limit by Surprise.

Authors:  Carlo Nicolini; Angelo Bifone
Journal:  Sci Rep       Date:  2016-01-14       Impact factor: 4.379

8.  Inverse Resolution Limit of Partition Density and Detecting Overlapping Communities by Link-Surprise.

Authors:  Juyong Lee; Zhong-Yuan Zhang; Jooyoung Lee; Bernard R Brooks; Yong-Yeol Ahn
Journal:  Sci Rep       Date:  2017-09-29       Impact factor: 4.379

9.  Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Authors:  Je-Yeon Yun; Premika S W Boedhoe; Chris Vriend; Neda Jahanshad; Yoshinari Abe; Stephanie H Ameis; Alan Anticevic; Paul D Arnold; Marcelo C Batistuzzo; Francesco Benedetti; Jan C Beucke; Irene Bollettini; Anushree Bose; Silvia Brem; Anna Calvo; Yuqi Cheng; Kang Ik K Cho; Valentina Ciullo; Sara Dallaspezia; Damiaan Denys; Jamie D Feusner; Jean-Paul Fouche; Mònica Giménez; Patricia Gruner; Derrek P Hibar; Marcelo Q Hoexter; Hao Hu; Chaim Huyser; Keisuke Ikari; Norbert Kathmann; Christian Kaufmann; Kathrin Koch; Luisa Lazaro; Christine Lochner; Paulo Marques; Rachel Marsh; Ignacio Martínez-Zalacaín; David Mataix-Cols; José M Menchón; Luciano Minuzzi; Pedro Morgado; Pedro Moreira; Takashi Nakamae; Tomohiro Nakao; Janardhanan C Narayanaswamy; Erika L Nurmi; Joseph O'Neill; John Piacentini; Fabrizio Piras; Federica Piras; Y C Janardhan Reddy; Joao R Sato; H Blair Simpson; Noam Soreni; Carles Soriano-Mas; Gianfranco Spalletta; Michael C Stevens; Philip R Szeszko; David F Tolin; Ganesan Venkatasubramanian; Susanne Walitza; Zhen Wang; Guido A van Wingen; Jian Xu; Xiufeng Xu; Qing Zhao; Paul M Thompson; Dan J Stein; Odile A van den Heuvel; Jun Soo Kwon
Journal:  Brain       Date:  2020-02-01       Impact factor: 13.501

Review 10.  Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning.

Authors:  Gennady M Verkhivker; Steve Agajanian; Guang Hu; Peng Tao
Journal:  Front Mol Biosci       Date:  2020-07-09
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