Course Evaluation Form

1. Course Evaluation Form • About The Course • -Go more slowly (||) • More lectures (||) • Problem Sets, Class Projects (|||) -Software tools • About The Instructor • -Accessible out of class (Office Hours, Thursdays 2pm-5pm) • Course Discussion

2. Networks in Biology

3. Today’s Lecture - The Cell as a Complex System -Types of Molecular Networks -Some Results on the Structure of Molecular Networks(Hierarchical Structure, Date and Party Hubs)- Disease Networks - Impacts of Social Networks in Biology

4. http://multimedia.mcb.harvard.edu/media.html Inner Life of the Cell

5. Bio-Map GENOME protein-gene interactions PROTEOME protein-protein interactions METABOLISM Bio-chemical reactions Citrate Cycle

6. METABOLISM Bio-chemical reactions Citrate Cycle

7. Boehring-Mennheim

8. Metab-movie Nodes: chemicals (substrates) Links: bio-chemical reactions Metabolic Network

9. Meta-P(k) Metabolic network Archaea Bacteria Eukaryotes Organisms from all three domains of life are scale-free networks! H. Jeong, B. Tombor, R. Albert, Z.N. Oltvai, and A.L. Barabasi, Nature, 407 651 (2000)

10. (a) Scale-free (b) Modular Modular vs. Scale-free Topology

11. Global network properties A.-L. B. and Z.N. Oltvai, Nat. Rev. Gen.(2004)

12. 3. Clustering coefficient scales # links between k neighbors C(k)= k(k-1)/2 Hierarchical Networks

13. Scaling of the clustering coefficient C(k) The metabolism forms a hierachical network. Ravasz, Somera, Mongru, Oltvai, A-L. B, Science 297, 1551 (2002).

14. Characterizing the links Metabolism: Flux Balance Analysis (Palsson) Metabolic flux for each reaction Edwards, J. S. & Palsson, B. O, PNAS 97, 5528 (2000). Edwards, J. S., Ibarra, R. U. & Palsson, B. O. Nat Biotechnol 19, 125 (2001). Ibarra, R. U., Edwards, J. S. & Palsson, B. O. Nature 420, 186 (2002).

15. Global flux organization in the E. coli metabolic network E. Almaas, B. Kovács, T. Vicsek, Z. N. Oltvai, A.-L. B. Nature, 2004.

17. Bio-Map GENOME protein-gene interactions PROTEOME protein-protein interactions METABOLISM Bio-chemical reactions Citrate Cycle

18. PROTEOME protein-protein interactions

19. Prot P(k) Topology of the protein network Nodes: proteins Links: physical interactions (binding) H. Jeong, S.P. Mason, A.-L. Barabasi, Z.N. Oltvai, Nature 411, 41-42 (2001)

20. Perfect copy Mistake: gene duplication Origin of the scale-free topology: Gene Duplication Proteins with more interactions are more likely to get a new link: Π(k)~k (preferential attachment). Wagner (2001); Vazquez et al. 2003; Sole et al. 2001; Rzhetsky & Gomez (2001); Qian et al. (2001); Bhan et al. (2002).

21. Prot- robustness Yeast protein network - lethality and topological position - Highly connected proteins are more essential (lethal)... H. Jeong, S.P. Mason, A.-L. Barabasi, Z.N. Oltvai, Nature 411, 41-42 (2001)

22. Protein Network Dynamics

25. Disease NetworksGenotypic Association Between Diseases

26. DISEASOME PHENOME GENOME Gene network Disease network

27. Disease Network Goh et al. PNAS 2007

28. Mental Diseases

29. P53 P(k) p53 network (mammals)

30. Lethal Genes Disease Genes Goh et al. PNAS 2007

31. Schematic functional organization Functional Periphery • Tissue-specific expression • Low degree • Low coexpression • Low lethality Functional Core • Expressed in most tissues (housekeeping) • High degree • High coexpression • Lethal Lack of disease genes Enrichment of disease genes

32. Phenotypic Association Between Diseases

34. Disease 1 Disease 2 Affect Same Individuals Significantly more than Random

35. Study Population ~ 13’039’018 patients ~ 32’341’348 records (hospitalizations)

36. Building a Net C12 N P1 P2

37. Word of Caution Perfectly correlated diseases, P2 = C12 Underestimates overlap of Common Phenotypes ~1 ~N Overestimate overlap of Rare Phenotypes

38. 1 Harley JB. Nature Genetics 39(9) 1053 (2007) 2 Scott LJ et al, Science 316 1341 (2007) Sibling having rheumatoid arthritis 1 Sibling having multiple sclerosis 1 First Degree Relatives Having Diabetes2

39. Building a Net C12 N P1 P2

40. Word of Caution Perfectly correlated diseases & P1 = P2 = C12 Perfectly correlated diseases & P1 >> P2 = C12 Example P2 = 1/10,000 P1 =1/100 If N >> P1, P2

41. Positive Associations Diseases appear are more likely to be correlated than anti-correlated

42. Visualizing the Network

46. http://hudine.neu.edu