
More than 70 publications using CentiScaPe!
See the complete list of publications 
Virtual knockout experiments on complex networks!
See the Interference Cytoscape plugin for experimental topology
A Cytoscape plugin for calculating network
centralities with numerical and graphical output:
New Features!
Centralities for directed networks (the edges have a direction as in metabolic and signal transduction networks)
Centralities for weighted networks (use experimental data set as weight for the edges of the network)
New Centralities added (Eigenvector, Bridging centrality and Edge betweenness)
Complex biological networks, such as intracellular signaling networks, are modeled by the evolution to accomplish a variety of different regulatory functions. This is achieved by controlling the overall topology of the network which, then, affects its dynamic behavior. Biological networks are hierarchichal, scalefree, modular structure in which few nodes, the hubs, play a particularly relevant topological role and this may reflect a critical role at biological level. However, also nodes with no or lower hub role may have critical regulatory role in certain biological phenomena. This could reflect nodespecific topological properties. Thus, it is of interest to categorize every nodes in a network by means of topological parameters allowing scoring of the nodes according to their individual topological relevance. Computation of centrality indexes may accomplish this goal. The centrality indexes are topological parameters allowing a nodebynode quantification of the reciprocal relationship between the nodes. This provides a classification of the nodes according to their capability to influence the function of other nodes in the network. Combination of this analysis with experimental data (node attributes) may help to identify critical nodes and regulatory circuits in a contextspecific manner.
The most complete Centralities Cytoscape plugin!
CentiScaPe computes centralities for undirected, directed and weighted networks:

Network parameters:

Diameter

Average Distance


Node parameters and their min, max and average values:

Eccentricity

Closeness

Betweenness

Stress

Centroid

Radiality

Eigenvector

Bridging Centrality


Edge parameters and their min, max and average values:

Edge Betweenness

Several kinds of graphical output
 Plot by centrality: Identify the nodes with high centrality values and integrate the analysis with biological attributes from lab experiment.
 Plot by node: Analyze single node centrality values
 Boolean highlight: Highlight nodes by their centrality values
More about CentiScaPe
 Documentation: CentiScaPe userguide, Centralities tutorial with definitions and biological meaning.
 How does people use CentiScaPe? See a list of publications using CentiScaPe.
Support CentiScaPe project!
If you publish result using CentiScaPe please cite:
"Analyzing biological network parameters with CentiScaPe"
Giovanni Scardoni; Michele Petterlini; Carlo Laudanna.
Bioinformatics 2009;
doi:10.1093/bioinformatics/btp517
This is really important for us!
authors:
Giovanni Scardoni, Gabriele Tosadori, Mohammed Faizaan, Franco Fabbri and Carlo Laudanna