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BioPathways SIG, July.29.2004. www.cytoscape.org Networks in Biology Molecular interaction and similarity networks are vital for understanding gene function.

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Presentation on theme: "BioPathways SIG, July.29.2004. www.cytoscape.org Networks in Biology Molecular interaction and similarity networks are vital for understanding gene function."— Presentation transcript:

1 BioPathways SIG, July.29.2004

2 www.cytoscape.org Networks in Biology Molecular interaction and similarity networks are vital for understanding gene function in biology How does my gene of unknown function relate to a known gene? Many biological questions can be answered by mapping the problem to a network problem

3 www.cytoscape.org Lots of Data to Analyze Network data is accumulating Protein-protein interactions, genetic pathways, metabolic networks, cell signals, gene regulations, similarity relationships, literature-based links Software to view and query this information is required to efficiently answer scientific questions

4 www.cytoscape.org Network Visualization Tools Pajek - Slovenia Osprey - SLRI, Toronto VisANT - BU Biolayout - EBI GraphViz PowerPoint Others Cytoscape (only open-source biology)

5 www.cytoscape.org What is Cytoscape? Cytoscape is a network visualization and analysis tool An extensible platform for bioinformatics software development New! 100% Open-source Java –GINY Graph Library Version 2.0 released this week: www.cytoscape.org

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7 www.cytoscape.org Example: Network Clustering Clusters in a protein-protein interaction network have been shown to represent protein complexes and parts of pathways Clusters in a protein similarity network represent protein families Network clustering is available through the MCODE Cytoscape plugin

8 Proteasome 26S Proteasome 20S Ribosome RNA Pol core RNA Splicing

9 www.cytoscape.org Cytoscape Core Features Visualize and lay out networks Display network data using visual styles Easily organize multiple networks Bird’s eye view navigation of large networks Supports SIF and GML, molecular profiling formats, node/edge attributes Functional annotation from GO + KEGG Metanodes (hyper graph / compound graph) Extensible through plugins (20 developed)

10 www.cytoscape.org Layout 16 algorithms available through plugins Zooming, hide/show, alignment

11 yFiles Organic

12 yFiles Circular

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14 www.cytoscape.org Visual Styles Map graph attributes to visual attributes Define visual styles for later use Graph has node and edge attributes E.g. expression data, interaction type, GO function Mapped to visual attributes E.g. node/edge size, shape, color, font… Take continuous gene expression data and visualize it as continuous node colors

15 Visual Styles Load “Your Favorite Network”

16 Visual Styles Load “Your Favorite Expression” Dataset

17 Visual Styles Map expression values to node colors using a continuous mapper

18 Visual Styles Expression data mapped to node colors

19 www.cytoscape.org Visual Styles Node attributes: node color, border color, border type, node shape, size, label, font Edge attributes: edge color, line types, arrows, label, font Multidimensional visual attribute mapping soon

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21 www.cytoscape.org Filters Multiple different filters are available Arbitrary Boolean combinations

22 www.cytoscape.org What can you use it for? Network visualization - multi-dimensional Network-based molecular profiling analysis –Transcriptionally active network modules Network clustering –Module and cluster detection Network comparison –PathBLAST

23 www.cytoscape.org Network Analysis Plugins for: –Networks and Transcriptional Profiling Active Modules (UCSD) Activity Centers (MSKCC) Expression Data Viewers (ISB) BioModules (ISB) –General network analysis MCODE: network clustering (MSKCC) PathBLAST (UCSD) –10 published papers –>10 in development

24 www.cytoscape.org Data Access Plugins for: –cPath / data services plugin (MSKCC) Poster at main meeting Recently available: –Control from Perl, Python, R (Cytotalk) –Data Cube Browser –BIND, PreBIND, HPRD access Open architecture for plugin development

25 Active Modules (UCSD) Ideker T, Ozier O, Schwikowski B, Siegel AF Bioinformatics. 2002;18 Suppl 1:S233-40

26 Active Modules

27 Biomodules (ISB) Prinz S, Avila-Campillo I, Aldridge C, Srinivasan A, Dimitrov K, Siegel AF, and Galitski T Genome Res. 2004 14: 380-390

28 www.cytoscape.org cPath (MSKCC)

29 Extensible Architecture: 100% open source Java –Core + plugin API –Plugins are independently licensed “Just need to write the algorithm” Template code samples Plugin

30 www.cytoscape.org Community Mailing lists cytoscape-announce@googlegroups.com cytoscape-discuss@googlegroups.com http://www.cytoscape.org 100% open source Contributions are encouraged

31 www.cytoscape.org MSK’s caBIG Pathway Plan High-quality, non-redundant human pathways Pathways (BioPAX)  cPath  Cytoscape BioPAX/PSI-MI represent pathway data Pathway DBs + curation support standards cPath merges BioPAX/PSI-MI datasets Cytoscape analyses pathway datasets in context with other data e.g. gene expression –Query/retrieve caCORE information via plugin –Link with other caBIG groups/tools

32 www.cytoscape.org MSK’s caBIG Pathway Plan High-quality, non-redundant human pathways Pathways (BioPAX)  cPath  Cytoscape BioPAX/PSI-MI represent pathway data Pathway DBs + curation support standards cPath merges BioPAX/PSI-MI datasets Cytoscape analyses pathway datasets in context with other data e.g. gene expression –Query/retrieve caCORE information via plugin –Link with other caBIG groups/tools

33 www.cytoscape.org Cytoscape Team Trey Ideker Nada Amin Ryan Kelley Dan Ramage Jonathan Wang Chris Workman Benno Schwikowski Hamid Bolouri Rowan Christmas Iliana Avila-Campillo Larissa Kamenkovich Andrew Markiel Paul Shannon Chris Sander Gary Bader Ethan Cerami Rob Sheridan


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