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CytoModeler: a tool for bridging large-scale network analysis and dynamic quantitative modeling.

Xia T, Van Hemert J, Dickerson JA - Bioinformatics (2011)

Bottom Line: CytoModeler is an open-source Java application based on the Cytoscape platform.It integrates large-scale network analysis and quantitative modeling by combining omics analysis on the Cytoscape platform, access to deterministic and stochastic simulators, and static and dynamic network context visualizations of simulation results.Implemented in Java, CytoModeler runs with Cytoscape 2.6 and 2.7.

View Article: PubMed Central - PubMed

Affiliation: Program of Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011, USA. netscape@iastate.edu

ABSTRACT

Summary: CytoModeler is an open-source Java application based on the Cytoscape platform. It integrates large-scale network analysis and quantitative modeling by combining omics analysis on the Cytoscape platform, access to deterministic and stochastic simulators, and static and dynamic network context visualizations of simulation results.

Availability: Implemented in Java, CytoModeler runs with Cytoscape 2.6 and 2.7. Binaries, documentation and video walkthroughs are freely available at http://vrac.iastate.edu/~jlv/cytomodeler/.

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Related in: MedlinePlus

(A) GAL network is constructed and imported in Cytoscape network panel. (B) The subnetwork community in the GAL network responsible for vesicular fusion is created by SubgraphCreator in a new network panel. Microarray data are imported and visualized in network context by OmicsAnalyzer. (C) A statistical correlation cluster calculation (Pearson's) was performed by OmicsAnalyzer according to the imported omics data. Two clusters were found and highlighted in cyan and red colors. (D) Original SEC9-SNC2-SSO2 network motif. (E) The motif was transformed into kinetic model by CytoModeler. (F) The original system is shown on the left. The middle graph shows the effect of a smaller initial concentration of tSNARE protein. The right side shows the effect of a large initial concentration of tSNARE protein which induces a high rate of fusion.
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Figure 1: (A) GAL network is constructed and imported in Cytoscape network panel. (B) The subnetwork community in the GAL network responsible for vesicular fusion is created by SubgraphCreator in a new network panel. Microarray data are imported and visualized in network context by OmicsAnalyzer. (C) A statistical correlation cluster calculation (Pearson's) was performed by OmicsAnalyzer according to the imported omics data. Two clusters were found and highlighted in cyan and red colors. (D) Original SEC9-SNC2-SSO2 network motif. (E) The motif was transformed into kinetic model by CytoModeler. (F) The original system is shown on the left. The middle graph shows the effect of a smaller initial concentration of tSNARE protein. The right side shows the effect of a large initial concentration of tSNARE protein which induces a high rate of fusion.

Mentions: Figure 1 shows how to perform the integrated analysis (from omics analysis to dynamics modeling) to a specific functional module of the network by using Cytoscape functional plug-in OmicsAnalyzer (Xia et al., 2010), SubgraphCreator and CytoModeler. As a proof of concept, we focused on a network motif Sec9-Snc1/2-Sso2 of the vesicular transport community of the Yeast galactose utilization (GAL) network (Ideker et al., 2001) (given in the Cytoscape sample data folder as ‘galFiltered.gml’) because the motif actually identifies protein interactions between SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins which are crucial players in vesicle transportation and exocytosis (Jahn and Scheller, 2006). First, by using SubgraphCreator, another Cytoscape plug-in developed by our group, we created a subnetwork for the vesicular transport community from the GAL network in Cytoscape. Secondly, OmicsAnalyzer was used to map omics data (given in the Cytoscape sample data folder as ‘galExpData.pvals’ file format) to the Sec9-Snc1/2-Sso2 network motif of the community network. Then, OmicsAnalyzer visualizes the imported data in a network context and examines the statistical correlation of the SNARE gene expressions. Finally, we connected omics analysis with dynamical modeling of the Sec9-Snc2-Sso2 motif using CytoModeler. We transformed the motif to a CytoModeler network by clicking ‘Create Model from Current Network’ button and adding the reaction equations through the reaction palette in the CytoModeler Model Editor. After adding in sample protein and reaction constant with parameters, we built a simulation-ready model for the network. Using the CytoModeler simulation interface with the built-in ODE solver, a fifth-order adaptive Runge-Kutta method, the in silico experiments successfully produced the previous observations (Scott et al., 2004), which shows how different initial concentrations of these SNARE proteins have large effects on the progression of membrane fusion.Fig. 1.


CytoModeler: a tool for bridging large-scale network analysis and dynamic quantitative modeling.

Xia T, Van Hemert J, Dickerson JA - Bioinformatics (2011)

(A) GAL network is constructed and imported in Cytoscape network panel. (B) The subnetwork community in the GAL network responsible for vesicular fusion is created by SubgraphCreator in a new network panel. Microarray data are imported and visualized in network context by OmicsAnalyzer. (C) A statistical correlation cluster calculation (Pearson's) was performed by OmicsAnalyzer according to the imported omics data. Two clusters were found and highlighted in cyan and red colors. (D) Original SEC9-SNC2-SSO2 network motif. (E) The motif was transformed into kinetic model by CytoModeler. (F) The original system is shown on the left. The middle graph shows the effect of a smaller initial concentration of tSNARE protein. The right side shows the effect of a large initial concentration of tSNARE protein which induces a high rate of fusion.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3102219&req=5

Figure 1: (A) GAL network is constructed and imported in Cytoscape network panel. (B) The subnetwork community in the GAL network responsible for vesicular fusion is created by SubgraphCreator in a new network panel. Microarray data are imported and visualized in network context by OmicsAnalyzer. (C) A statistical correlation cluster calculation (Pearson's) was performed by OmicsAnalyzer according to the imported omics data. Two clusters were found and highlighted in cyan and red colors. (D) Original SEC9-SNC2-SSO2 network motif. (E) The motif was transformed into kinetic model by CytoModeler. (F) The original system is shown on the left. The middle graph shows the effect of a smaller initial concentration of tSNARE protein. The right side shows the effect of a large initial concentration of tSNARE protein which induces a high rate of fusion.
Mentions: Figure 1 shows how to perform the integrated analysis (from omics analysis to dynamics modeling) to a specific functional module of the network by using Cytoscape functional plug-in OmicsAnalyzer (Xia et al., 2010), SubgraphCreator and CytoModeler. As a proof of concept, we focused on a network motif Sec9-Snc1/2-Sso2 of the vesicular transport community of the Yeast galactose utilization (GAL) network (Ideker et al., 2001) (given in the Cytoscape sample data folder as ‘galFiltered.gml’) because the motif actually identifies protein interactions between SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins which are crucial players in vesicle transportation and exocytosis (Jahn and Scheller, 2006). First, by using SubgraphCreator, another Cytoscape plug-in developed by our group, we created a subnetwork for the vesicular transport community from the GAL network in Cytoscape. Secondly, OmicsAnalyzer was used to map omics data (given in the Cytoscape sample data folder as ‘galExpData.pvals’ file format) to the Sec9-Snc1/2-Sso2 network motif of the community network. Then, OmicsAnalyzer visualizes the imported data in a network context and examines the statistical correlation of the SNARE gene expressions. Finally, we connected omics analysis with dynamical modeling of the Sec9-Snc2-Sso2 motif using CytoModeler. We transformed the motif to a CytoModeler network by clicking ‘Create Model from Current Network’ button and adding the reaction equations through the reaction palette in the CytoModeler Model Editor. After adding in sample protein and reaction constant with parameters, we built a simulation-ready model for the network. Using the CytoModeler simulation interface with the built-in ODE solver, a fifth-order adaptive Runge-Kutta method, the in silico experiments successfully produced the previous observations (Scott et al., 2004), which shows how different initial concentrations of these SNARE proteins have large effects on the progression of membrane fusion.Fig. 1.

Bottom Line: CytoModeler is an open-source Java application based on the Cytoscape platform.It integrates large-scale network analysis and quantitative modeling by combining omics analysis on the Cytoscape platform, access to deterministic and stochastic simulators, and static and dynamic network context visualizations of simulation results.Implemented in Java, CytoModeler runs with Cytoscape 2.6 and 2.7.

View Article: PubMed Central - PubMed

Affiliation: Program of Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011, USA. netscape@iastate.edu

ABSTRACT

Summary: CytoModeler is an open-source Java application based on the Cytoscape platform. It integrates large-scale network analysis and quantitative modeling by combining omics analysis on the Cytoscape platform, access to deterministic and stochastic simulators, and static and dynamic network context visualizations of simulation results.

Availability: Implemented in Java, CytoModeler runs with Cytoscape 2.6 and 2.7. Binaries, documentation and video walkthroughs are freely available at http://vrac.iastate.edu/~jlv/cytomodeler/.

Show MeSH
Related in: MedlinePlus