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Graph properties of biological networks

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Graph properties of biological networks

  1. 1. Graph properties of biological networks Modeling of Biological Systems UCSF, May 8 2009 natali.gulbahce@gmail.com
  2. 2. Chemotaxis via differential equations
  3. 3. Cell cycle via Boolean modeling
  4. 4. Large-scale cellular networks • Transcriptional factor binding networks • Protein-protein interaction networks • Metabolic networks • Protein phosphorylation networks • Genetic interaction networks
  5. 5. Numbers Zhu et al. Gen. & Dev. (2007)
  6. 6. Transcription factor binding networks Sea urchin: Davidson et al. 2002 Large scale identification of TF-binding sites using ChIP-chip or DNA sequencing Yeast and mammalian cells: Horak and Snyder 2005; Kim et al.; Wei et al 2006.
  7. 7. Human Interactome Protein Y2H (Rual et al.) Literature Yeast: Yu et al. 2008; Krogan et al. Human: Rual et al 2005; Stelzl et al 2005. 2006; Gavin et al. 2006; Ito et al Drosophila: Giot et al. 2003. 2001; Uetz et al 2000. C. elegans: Li et al 2004.
  8. 8. E. Coli Metabolic Network Nodes: metabolites Edges: reactions Kegg, Wit, Biocyc, Bigg (UCSD)
  9. 9. Yeast phosphorylome Kinase Substrate Yeast: Ptacek et al. 2005 H. Sapiens: Linding et al. 2007 Phospho.elm
  10. 10. Yeast genetic interaction network Tong et al. 2001; Roguev et al. 2007.
  11. 11. Why study these large scale networks?
  12. 12. In this class • Network measures: degree, clustering, assortativity, betweenness centrality, motifs, modularity. • Networks: random, small world, scale-free. • Simple models, essentiality, topological robustness.
  13. 13. Human interactome follows a power-law HUBS Distribution is the same without the bias introduced by well- studied proteins.
  14. 14. Yeast ; Zhu et al. Gen. & Dev. (2007)
  15. 15. Assortativity • A preference for a network's nodes to attach to others that are similar or different in degree. Maslov and Sneppen, 2002. P(K0,K1)/PR(K0,K1) Yeast interactome Yeast transcriptome
  16. 16. Non-Hub Bottleneck in Yeast Interactome Cak1p is a cyclin- dependent kinase- activating kinase involved in two key signaling pathways.
  17. 17. Hubs, bottlenecks: which are more essential? NH-NB: Non-hub, non-bottleneck; H-NB: Hub, non-bottleneck; B-NH: Bottleneck, non-hub; BH: Bottleneck, hub. Yu et al. 2007.
  18. 18. Watts and Strogatz, Nature (1998).
  19. 19. Milo et al Science 2002
  20. 20. How to randomize a network Network randomization is used to determine the statistical significance of a quantity, or how happy you should be about a research result. • Shuffle everything. • Conserve the degree. • Conserve the connectedness of the network.
  21. 21. Cfinder www.cfinder.org Palla et al. Nature (2005).
  22. 22. Error and attack tolerance d f f Albert et al. Nature (2000).
  23. 23. Date hubs vs. party hubs Non-hubs Hubs Hubs (random)
  24. 24. Date hubs vs. party hubs Date hubs organize the proteome, connecting biological processes—or modules—to each other, whereas party hubs function inside modules.
  25. 25. May 17 Swine Flu prediction gleamviz.org
  26. 26. Further References • Barabasi and Oltvai, “Network biology: understanding the cell’s functional organization,” Nature Reviews Genetics, 2004. • Zhu, Gerstein and Snyder, “Getting connected: analysis and principles of biological networks,” Genes and Development, 2007.