CINNA: an R/CRAN package to decipher Central Informative Nodes in Network Analysis.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
15 04 2019
15 04 2019
Historique:
received:
09
05
2018
revised:
06
09
2018
accepted:
18
09
2018
pubmed:
22
9
2018
medline:
19
2
2020
entrez:
22
9
2018
Statut:
ppublish
Résumé
Centrality analysis involves a series of ambiguities in that there are numerous well-known centrality measures with differing algorithms for establishing which nodes in a network are essential. There is no clearly preferred measure or means of deciding which measure is most germane to a given network with respect to node essentiality vis-à-vis topological features. Our aim here was to develop an instrument that enables comparisons among potentially appropriate centrality measures to be made with respect to network structure and thereby to support the identification of the most informative measure according to dimensional reduction methods. The Central Informative Nodes in Network Analysis (CINNA) package introduced herein gathers all required functions for centrality analysis in weighted/unweighted and directed/undirected networks. Then, it compares, assorts and visualizes centrality measures to select which best describes the node importance. CINNA is available in CRAN, including a tutorial. URL: https://cran.r-project.org/web/packages/CINNA/index.html.
Identifiants
pubmed: 30239607
pii: 5102873
doi: 10.1093/bioinformatics/bty819
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1436-1437Informations de copyright
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.