cytoHubba

Predicts and explores important nodes and subnetworks in a given network by several topological algorithms.
<p>Explore important nodes/hubs and fragile motifs in an interactome network by several topological algorithms including Degree, Edge Percolated Component (EPC), Maximum Neighborhood Component (MNC), Density of Maximum Neighborhood Component (DMNC), Maximal Clique Centrality (MCC) and centralities based on shortest paths, such as Bottleneck (BN), EcCentricity, Closeness, Radiality, Betweenness, and Stress.</p>

0.1

Works with Cytoscape 3.0

Release Notes

We introduce a novel **Cytoscape 3.x plugin** **cytoHubba** for ranking nodes in a network by their network features. CytoHubba provides 11 topological analysis methods including Degree, Edge Percolated Component (EPC), Maximum Neighborhood Component(MNC), Density of Maximum Neighborhood Component (DMNC), Maximal Clique Centrality (MCC) and six centralities (Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, and Stress) based on shortest paths. Among the 11 methods, the newly proposed method **MCC** performs better than the others. MCC captures more essential proteins in the top ranked list in both high-degree and low-degree proteins. Another method, **DMNC**, catches different set of essential proteins suggesting it scores the network in different way. Since the biological network is heterogeneous, it is reasonable to use more than one method for catching essential proteins. We hope this handy tool can serve as good starting points to new therapies and novel insights in understanding basic mechanisms controlling normal cellular processes and disease pathologies.

CYTOSCAPE 3

Version 0.1

Released 4 Jan 2017

Works with Cytoscape 3.0

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