Biological network analysis with CentiScaPe: centralities and experimental dataset integration

F1000Res. 2014 Jul 1:3:139. doi: 10.12688/f1000research.4477.2. eCollection 2014.

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.

Keywords: Cytoscape; centrality indexes; networks; nodes; topological analysis.

Grants and funding

This work was supported by: Italian Association for Cancer Research (AIRC, IG 8690) (C.L.); Fondazione Cariverona; Nanomedicine project University of Verona and Fondazione Cariverona (C.L.). Directed centralities have been developed thanks to the GSoC2013 program.