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CentiServer: A Comprehensive Resource, Web-Based Application and R Package for Centrality Analysis

Author

Listed:
  • Mahdi Jalili
  • Ali Salehzadeh-Yazdi
  • Yazdan Asgari
  • Seyed Shahriar Arab
  • Marjan Yaghmaie
  • Ardeshir Ghavamzadeh
  • Kamran Alimoghaddam

Abstract

Various disciplines are trying to solve one of the most noteworthy queries and broadly used concepts in biology, essentiality. Centrality is a primary index and a promising method for identifying essential nodes, particularly in biological networks. The newly created CentiServer is a comprehensive online resource that provides over 110 definitions of different centrality indices, their computational methods, and algorithms in the form of an encyclopedia. In addition, CentiServer allows users to calculate 55 centralities with the help of an interactive web-based application tool and provides a numerical result as a comma separated value (csv) file format or a mapped graphical format as a graph modeling language (GML) file. The standalone version of this application has been developed in the form of an R package. The web-based application (CentiServer) and R package (centiserve) are freely available at http://www.centiserver.org/

Suggested Citation

  • Mahdi Jalili & Ali Salehzadeh-Yazdi & Yazdan Asgari & Seyed Shahriar Arab & Marjan Yaghmaie & Ardeshir Ghavamzadeh & Kamran Alimoghaddam, 2015. "CentiServer: A Comprehensive Resource, Web-Based Application and R Package for Centrality Analysis," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-8, November.
  • Handle: RePEc:plo:pone00:0143111
    DOI: 10.1371/journal.pone.0143111
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    References listed on IDEAS

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    1. Gabor I Simko & Peter Csermely, 2013. "Nodes Having a Major Influence to Break Cooperation Define a Novel Centrality Measure: Game Centrality," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-8, June.
    2. Mahendra Piraveenan & Mikhail Prokopenko & Liaquat Hossain, 2013. "Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-14, January.
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    5. Gündüç, Semra & Eryiğit, Recep, 2021. "Time dependent correlations between the probability of a node being infected and its centrality measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).

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