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= Your Title = '''Your name ''' |
= Power Graph Analysis with CyOog = '''Matthias Reimann ''' |
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| ''Your institute'' | ''Biotechnology Center, Technische Universität Dresden, Germany'' |
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| '''__Biological Use Case__''': Describe a real biological problem. |
'''__Biological Use Case__''': ''General:'' Analysis of gigantic biological networks like protein interaction networks, sequence homology networks, or regulatory networks. The information you are looking for in such networks is hidden by a big mass of edges -- inside a 'fur ball' or 'hairy monster'. Instead of loosing valuable details in the networks by coarse-graining them using clustering techniques, Power Graph Analysis can be used. A power graph is a compressed version of a normal graph. The used transformation is completely reversible. ''Example described here:'' Finding functional relationships among transcription factors in a huge regulatory network. |
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| ''__Cytoscape version__'': Version number (2.6) | ''__Cytoscape version__'': Version number (2.6) |
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| ''__Plugins to Load__'': Plugins and urls | ''__Plugins to Load__'': CyOog: http://www.biotec.tu-dresden.de/schroeder/group/powergraphs |
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| ''__GUI steps__'': | ''__GUI steps__'': |
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| '''__Data / Session Files__''': Attach (preferably) a session file or else the data files used in the workflow | |
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| '''__Presentation__''': Attach your presentation | '''__Data / Session Files__''': Attach (preferably) a session file or else the data files used in the workflow |
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| '''__Webstart__''': Attach a webstart | '''__Presentation__''': Attach your presentation |
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| '''__Video__''': Attach a video link |
'''__Webstart__''': http://www.biotec.tu-dresden.de/schroeder/group/powergraphs/download_cyplugin.html ''It is still necessary to load session file separately!'' |
Power Graph Analysis with CyOog
Matthias Reimann
Biotechnology Center, Technische Universität Dresden, Germany
Biological Use Case:
General: Analysis of gigantic biological networks like protein interaction networks, sequence homology networks, or regulatory networks. The information you are looking for in such networks is hidden by a big mass of edges -- inside a 'fur ball' or 'hairy monster'. Instead of loosing valuable details in the networks by coarse-graining them using clustering techniques, Power Graph Analysis can be used. A power graph is a compressed version of a normal graph. The used transformation is completely reversible.
Example described here: Finding functional relationships among transcription factors in a huge regulatory network.
Recipe
Cytoscape version: Version number (2.6)
Plugins to Load: CyOog: http://www.biotec.tu-dresden.de/schroeder/group/powergraphs
GUI steps:
Describe each step (story), the GUI action to take, and probable remarks
Story |
Action |
Remarks |
|
|
|
Data / Session Files: Attach (preferably) a session file or else the data files used in the workflow
Presentation: Attach your presentation
Webstart:
http://www.biotec.tu-dresden.de/schroeder/group/powergraphs/download_cyplugin.html
It is still necessary to load session file separately!