Biological network analysis with CentiScaPe: centralities and experimental dataset integration
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Published on: November 17, 2019
Giovanni Scardoni1, Gabriele Tosadori1, Mohammed Faizan2
1Center for Biomedical Computing, University of Verona, Verona, 37134, Italy.
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.
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