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Discussion summary Cytoscape introduction

Discussion summary Cytoscape introduction. Thomas Skøt Jensen Center for Biological Sequence Analysis The Technical University of Denmark. Sub-cellular localization coverage. Co-localization of interacting proteins. Tendency to interact with your cousin.

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Discussion summary Cytoscape introduction

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  1. Discussion summaryCytoscape introduction Thomas Skøt Jensen Center for Biological Sequence Analysis The Technical University of Denmark

  2. Sub-cellular localization coverage

  3. Co-localization of interacting proteins

  4. Tendency to interact with your cousin

  5. Over-representation of highly abundant proteins

  6. say a lot, of which most is wrong say a lot, of which most is right say little, of which most is wrong say little, of which most is right Coverage versus Accuracy Sensitivity Specificity

  7. Visualizing protein/gene relationships A short introduction to Cytoscape

  8. Outline • Visualization • Why Cytoscape? • Getting started • Attributes for nodes and edges • Examples

  9. Visualization • Systems Biology - looking at a system • a collection of units (gene/proteins) in a context • Massive amounts of protein/gene relationships • a lot of undiscovered biology is hiding in that data • impossible to get an overview if investigated by hand • Integrate many types of relationships • the data is available in the CBS data warehouse

  10. Why Cytoscape? • Cytoscape (www.cytoscape.org) • can visualize relationships • is easy to use • has an advanced color coding scheme • allows for custom made plug-ins • has a strong community • is free for academia

  11. Getting started • Two types of input formats • GML: a graphical markup language • SIF: a simple input format • Nodes (genes/proteins) and relationships are specified in one file

  12. GML - node • GML example: node [ id 37 label "37" graphics [ x 411.0 y 395.0 h 34.0 w 122.0 fill "#ccccff" type "rectangle" ] ]

  13. GML - edge • GML example: edge [ source 210 target 92 label "PPo" graphics [ width 1.0 type "line" fill "#000000" ] ]

  14. SIF • Very simple node_1 edge_label node_2 node_3 edge_label node_2 node_4 edge_label node_2 node_5 edge_label node_6 node_7 edge_label node_1

  15. SIF SIF Example : protein-protein interactions in yeast YDL224C pp YER059W YDL224C pp YIL050W YDL224C pp YML064C YDL224C pp YNL189W YDR386W pp YBR009C YDR386W pp YBR098W YDR386W pp YCL032W YDR386W pp YDL043C YDR386W pp YDL208W YDR386W pp YDR363W YDR386W pp YDR381W YDR386W pp YER006W

  16. Node and edge attributes • Coloring based on attributes • Nodes; cell cycle regulated, tissue type, etc. • Edges; ppi, protein-DNA, etc. • Expression data Node_id exp1 exp2 exp3 exp4 ... ... ...

  17. Node annotation YeastCompartment YAL001C = transcription factor TFIIIC complex YAL002W = membrane fraction YAL003W = ribosome YAL005C = cytoplasm* YAL007C = COPII-coated vesicle YAL008W = mitochondrion YAL009W = integral to membrane* YAL010C = mitochondrial outer membrane YAL011W = nucleus

  18. Node annotation CellCycleRegulated YAL001C = 1 YAL007C = 1 YAL012W = 1 YAL021C = 1 YAL022C = 1 YAL023C = 1 YAL024C = 1 YAL034W-A = 1 YAL039C = 1 YAL040C = 1 YAL053W = 1 YAL067C = 1

  19. Edge annotation Protein-DNA binding data MBF pd YER059W MBF pd YIL050W MBF pd YML064C YML064C pd YNL189W YML064C pd YER059W YML064C pd YBR098W YBR098W pd YCL032W YBR098W pd YDL043C YDL043C pd YDL208W YDL043C pd YDR363W YDL208W pd YDR381W YDL208W pd YML064C Edge annotation: ActivationRepression MBF (pd) YER059W = 1 MBF (pd) YIL050W = 0 MBF (pd) YML064C = 1 YML064C (pd) YNL189W = 0 YML064C (pd) YER059W = 0 YML064C (pd) YBR098W = 1 YBR098W (pd) YCL032W = 0 YBR098W (pd) YDL043C = 1 YDL043C (pd) YDL208W = 1 YDL043C (pd) YDR363W = 1 YDL208W (pd) YDR381W = 1 YDL208W (pd) YML064C = 0

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