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Biological network analysis with CentiScaPe: centralities and experimental dataset integration [v2; ref status: indexed, http://f1000r.es/55u]

Authors :
Giovanni Scardoni
Gabriele Tosadori
Mohammed Faizan
Fausto Spoto
Franco Fabbri
Carlo Laudanna
Source :
F1000Research, Vol 3 (2015)
Publication Year :
2015
Publisher :
F1000 Research Ltd, 2015.

Abstract

The growing dimension and complexity of the available experimental data generating biological networks have increased the need for tools that help in categorizing nodes by their topological relevance. Here we present CentiScaPe, a Cytoscape app specifically designed to calculate centrality indexes used for the identification of the most important nodes in a network. CentiScaPe is a comprehensive suite of algorithms dedicated to network nodes centrality analysis, computing several centralities for undirected, directed and weighted networks. The results of the topological analysis can be integrated with data set from lab experiments, like expression or phosphorylation levels for each protein represented in the network. Our app opens new perspectives in the analysis of biological networks, since the integration of topological analysis with lab experimental data enhance the predictive power of the bioinformatics analysis.

Subjects

Subjects :
Bioinformatics
Medicine
Science

Details

Language :
English
ISSN :
20461402
Volume :
3
Database :
Directory of Open Access Journals
Journal :
F1000Research
Publication Type :
Academic Journal
Accession number :
edsdoj.9e058543ce29411f9fb25f9104e77c6c
Document Type :
article
Full Text :
https://doi.org/10.12688/f1000research.4477.2