CentiScaPe is a Cytoscape app that computes network centrality parameters. It is the most complete Cytoscape app for network centralities calculating Degree, Average Shortest Path, Eccentricity, Closeness, Betweenness, Centroid, Stress, Radiality, Eigenvector, Edge Betweenness, Bridging Centrality, for directed and undirected networks. CentiScaPe allows identifying network nodes that are relevant from both experimental and topological viewpoints. CentiScaPe also provides a Boolean logic- based tool that allows easy characterization of nodes whose topological relevance depends on more than one centrality. Finally, different graphic outputs and the included description of biological significance for each computed centrality facilitate the analysis by the end users not expert in graph theory, thus allowing easy node categorization and experimental prioritization.
Goal
CentiScaPe can provide only static analysis of a network. We want to develop a tool that can compute semi-dynamic simulation, particularly the [SIR model](SIR model). The SIR model is a Compartmental model used in epidemiology to simulate the establishment and spread of infectious diseases. It serves as a base mathematical framework for understanding the complex dynamics of such system. Population is divided in three states: susceptible to the infection of the pathogen (often denoted by S), infected by the pathogen (given the symbol I) and recovered/removed/immune (denoted R). The way that these compartments interact is often based on a network model, hence the idea to include the SIR model in the CentiScaPe tool for network analysis
khanspers
commented
5 years ago
Background
CentiScaPe is a Cytoscape app that computes network centrality parameters. It is the most complete Cytoscape app for network centralities calculating Degree, Average Shortest Path, Eccentricity, Closeness, Betweenness, Centroid, Stress, Radiality, Eigenvector, Edge Betweenness, Bridging Centrality, for directed and undirected networks. CentiScaPe allows identifying network nodes that are relevant from both experimental and topological viewpoints. CentiScaPe also provides a Boolean logic- based tool that allows easy characterization of nodes whose topological relevance depends on more than one centrality. Finally, different graphic outputs and the included description of biological significance for each computed centrality facilitate the analysis by the end users not expert in graph theory, thus allowing easy node categorization and experimental prioritization.
Goal
CentiScaPe can provide only static analysis of a network. We want to develop a tool that can compute semi-dynamic simulation, particularly the [SIR model](SIR model). The SIR model is a Compartmental model used in epidemiology to simulate the establishment and spread of infectious diseases. It serves as a base mathematical framework for understanding the complex dynamics of such system. Population is divided in three states: susceptible to the infection of the pathogen (often denoted by S), infected by the pathogen (given the symbol I) and recovered/removed/immune (denoted R). The way that these compartments interact is often based on a network model, hence the idea to include the SIR model in the CentiScaPe tool for network analysis
Technology and Skills
Cytoscape, CentiScaPe, Java
Potential Mentors
Giovanni Scardoni (CBMC, University of Verona)
Contact
cytoscape-discuss@googlegroups.com, giovanni.scardoni@gmail.com