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Biological network analysis with CentiScaPe: centralities and experimental dataset integration

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 u...

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Detalles Bibliográficos
Autores principales: Scardoni, Giovanni, Tosadori, Gabriele, Faizan, Mohammed, Spoto, Fausto, Fabbri, Franco, Laudanna, Carlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647866/
https://www.ncbi.nlm.nih.gov/pubmed/26594322
http://dx.doi.org/10.12688/f1000research.4477.2
Descripción
Sumario: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.