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Hubba: Hub Objects Analyzer—A Framework of Interactome Hubs Identification for Network Biology

Hubba: Hub Objects Analyzer—A Framework of Interactome Hubs Identification for Network Biology. 吳 信 宏 , Hsin-Hung Wu eastc228@iis.sinica.edu.tw Laboratory of System Biology and Network Biology Institute of Information Science, Academic Sinica

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Hubba: Hub Objects Analyzer—A Framework of Interactome Hubs Identification for Network Biology

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  1. Hubba: Hub Objects Analyzer—A Framework of Interactome Hubs Identification for Network Biology 吳 信 宏, Hsin-Hung Wu eastc228@iis.sinica.edu.tw Laboratory of System Biology and Network Biology Institute of Information Science, Academic Sinica Department of Computer Science and Information Engineering, NTU July 24, 2009

  2. Outline • Network Summary • What Does Hubba Do • Hubba Methods • Web Demo & cyto-Hubba

  3. Network Structure • Network includes: • Nodes • Edges • Node: • Person、web page 、station、destination • Edge: • Relationship 、internet connection 、traffic path

  4. Traffic Network

  5. World Wide Web

  6. Human relationship

  7. Protein interaction network • Protein interaction network • Node → protein • Edge → interaction Information inside a PPI network

  8. What kind of information ?

  9. Yeast Protein Interaction Network • 1870 proteins • 2240 interactions Hubs、pathways、complexes Barabási A. L. et al., Nature 2001

  10. What Does Hubba Do? • A web-based service • http://hub.iis.sinica.edu.tw/Hubba/ • Exploring the essential nodes by 6 methods • Each method gives one score (rank) to each protein • Visualizing the results in a user-friendly mode • Subgraph • First-level neighbors • Shortest path among proteins

  11. Concept of Hubba Complex Pathway Hubba Hubs PPI network Subnetwork

  12. Hubba (http://hub.iis.sinica.edu.tw/Hubba/)

  13. The Input Format • PSI • Tab-delimited • Tab-delimited with weight

  14. PSI

  15. Tab-delimited The input : A B A C A D A G A H B A B C B F C A C B D A E F E H F B F G G A G F H A H E

  16. Tab-delimited with weight The input : A B 0.9 A C 0.9 A D 0.5 A G 1 A H 0.2 B A 0.9 B C 1 B F 0.7 C A 0.9 C B 1 D A 0.5 E F 0.8 E H 0.3 F B 0.7 F G 0.4 G A 1 G F 0.4 H A 0.2 H E 0.3 0.7 1 0.9 0.4 0.8 1 0.9 0.5 0.2 0.3

  17. Algorithms (topological) • Degree (2001) • BottleNeck (2004, 2007) • Edge Percolation Component (EPC) (2003) • Subgraph Centrality (SC) (2006) • Maximum Neighborhood Component (MNC) • Density of Maximum Neighborhood Component (DMNC) • Double Screening Scheme (DSS)

  18. DSS in Hubba • MNC and DMNC are selected: • Choose 2*n the top nodes in MNC • Rank the selected nodes (2*n) again in DMNC • Output the first n nodes (DSS result)

  19. Cyto-Hubba http://www.cytoscape.org/ Utilize Hubba with other plug-in Compute the Hubba Score Additional information Hubba analysis

  20. Now You Know.. Hubba helps you find out the essential candidates

  21. Demo • Hubba: • http://hub.iis.sinica.edu.tw/Hubba/ • cyto-Hubba: • http://hub.iis.sinica.edu.tw/cyto-Hubba/

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