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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 networks. Known visualization tools. Pajek (V. Batagelj 1998) Medusa (Sean D. Hooper 2005)

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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 networks

  2. Known visualization tools • Pajek (V. Batagelj 1998) • Medusa (Sean D. Hooper 2005) • Ondex (Kohler J 2006) Other programs: • Osprey (Breitkreutz 2003) • Cytoscape (Shannon 2003) • MAPMAN (Thimm 2004) • Shark (Pinney 2005) • CNPlot (Batada 2004)

  3. Large scale networks What if the network is a bit bigger with many connections ???????????????????????????

  4. General goal A C • Flexible 3D interactive visualization tool for heterogeneous data types • Clustering Analysis • Simple and generic way for data input • Example of input file • Extraction of connections • Direct Connection • Indirect Connection B C A B A C

  5. Outline • Let’s see how it works

  6. Snapshots-1

  7. Snapshots-2 (Clustering)

  8. What was done last year • Rewriting big part of the code • 5 clustering algorithms were added • Detection of indirect connetions • Allowing rotations of the layers around themselves • Integrated tree viewers like ATV

  9. What was done last year • Performance improvement (faster – lower memory) • Much better graphics • VRML compatibility • Crossovers was solved by • Allowing specific rotations to • each layer

  10. Future Work Biology oriented AKSproceeds as a regular search engine that looks for desired query terms into existing scientific knowledge; it also performs a conceptual search, meaning that whether the terms found possess a relevant biological meaning, the system will retrieve all documents where that term is present in any of its conceptual definitions SRSis a platform for life-science database and application integration, providing rapid, easy and user-friendly access to the large volumes of diverse data stored in over 1000 internal and public domain databases.

  11. Future Work

  12. Acknowledgements Reinhard Schneider (Group Leader) Venkata Satagopam (SRS administrator) Theodoros Soldatos (Text mining) Evangelos Pafilis (Web Services) Seán O'Donoghue

  13. Acknowledgements Thank you!

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