[HTML][HTML] Biological network analysis with CentiScaPe: centralities and experimental dataset integration

G Scardoni, G Tosadori, M Faizan, F Spoto… - …, 2014 - ncbi.nlm.nih.gov
G Scardoni, G Tosadori, M Faizan, F Spoto, F Fabbri, C Laudanna
F1000Research, 2014ncbi.nlm.nih.gov
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 …
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.
ncbi.nlm.nih.gov