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Data integration & knowledge management group Structural and Computational Biology unit

Data integration & knowledge management group Structural and Computational Biology unit. Georgios Pavlopoulos. A visualization tool for high level relationship and clustering analysis in large scale networks. Known visualization tools. Pajek. NetDraw. HyperGraph. Ondex. MultiNet.

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Data integration & knowledge management group Structural and Computational Biology unit

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  1. Data integration & knowledge management group Structural and Computational Biology unit Georgios Pavlopoulos A visualization tool for high level relationship and clustering analysis in large scale networks

  2. Known visualization tools Pajek NetDraw HyperGraph Ondex MultiNet Cytoscape Medusa Negopy GraphViz SocNetV Plankton Otter Tulip Osprey

  3. Large scale networks What if the network is a bit bigger with many connections? Is there any way to visualize some clusters out of this mess?

  4. Motivation – General goal 1.Interactive 2.Visualize everything in 3D 3.Combine different kinds of data under the same Network 4.Provide and Visualize some clustering algorithms

  5. Motivation – General goal A C 5.Keep it generic so that it can be used in any case study 6.Keep it compatible with already existing tools 7.Maintain it read a very simple input file format 8.Extract indirect connections – Find hidden information Direct connection B C Indirect connection Between A-C A B A C

  6. Arena3D

  7. …about Arena3D • Tree based clustering algorithms: • UPGMA • NJ • HCL • Non-Tree based clustering algorithms: • MCL (not yet) • Affinity Propagation • K-Means

  8. Input file example Input file example: node_i:layer _x node_j:layer_y weight A:pathways B:pathways 5.61 A:pathwaysA:chemicals 1.2 B:chemicals A:diseases 4.3 A:diseases C:proteins 2.7 …

  9. Overview – My part Visualization Text Mining Databases public data EMBL

  10. Connectivity with SRS Evangelos Pafilis Web Servises

  11. SRS: data integration system • > 80 databases in EMBL Heidelberg • queries against multiple databases • cross-linking between the records Venkata Satagopam http://srs.embl.de

  12. Connectivity with Bioalma Visualization Evangelos Pafilis Text Mining Databases public data EMBL

  13. bioalma: query

  14. bioalma: analysis creation

  15. entity recognition & co-occurrences

  16. bioalma:analysis report, cooccurrences

  17. bioalma:analysis report, cooccurrences

  18. Overview Visualization USER Text Mining Databases public data EMBL

  19. DEMO VIDEO - DEMONSTRATION

  20. Snapshots

  21. Snapshots

  22. What I did last year • Better graphics • More interactive • Increase memory and speed performance • Simpler GUI • Directed graphs support • Moving layers in 3D space • Clustering Algorithms – individual layers • Clustering algorithms – layer combination • PREDEFINED clustering • Indirect Connections • Integration with SRS • Integration with Bioalma Text Mining

  23. What is next? • Data analysis • Mitocheck • Anne Claude • Tamahud project • Bioquant project • Functionality • SBML support • Even more interactivity – make everything clickable • Minimization of crossovers • Apply the same functionality to Medusa-2D • Sub-Network selection • Future plan • Publication • EMBLEM license – invention record form

  24. Group Members - Acknowledgements

  25. Thank you !

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