1. Biological networks Tutorial 12

2. Protein-Protein interactions –STRING Protein and genetic interactions –BioGRID Network visualization –Cytoscape Cool story of the day How to model natural selection Biological networks

3. Protein Protein interactions (PPI) http://string-db.org/

4. Protein Protein interactions (PPI)

9. Will change according to the prediction method you choose.

10. Protein Protein interactions (PPI)

14. Protein and genetic interactions http://thebiogrid.org/

15. Protein and genetic interactions

18. Signaling pathways Hearing and vision map

19. Network visualization - Cytoscape http://www.cytoscape.org/

20. Network visualization - Cytoscape The input is a tab delimited file:

21. Network visualization - Cytoscape

25. Degree: the number of edges that a node has. The node with the highest degree in the graph

26. Network visualization - Cytoscape Closeness: measure how close a node to all other nodes in the network. The nodes with the highest closeness

27. Network visualization - Cytoscape The node with the highest betweenness Betweenness: quantify the number of all shortest paths that pass through a node.

28. Network visualization - Cytoscape Know your network type: Directed – for regulatory networks Undirected – for protein-protein networks

29. Network visualization - Cytoscape (Analysis of another network)

30. Network visualization - Cytoscape Highest degree = big Highest betweens = red

31. Network visualization - Cytoscape Cytoscape has ~200 plugins http://chianti.ucsd.edu/cyto_web/plugins/

32. Cool Story of the day How to model natural selection

34. Natural Selection Consider a biological system whose phenotypes are defined by v quantitative traits (such as bird beak length and not DNA sequences). Most theories of natural selection maximize a specific fitness function F(v) resulting in an optimal phenotype – a point in morpho-space. But, in many cases organisms need to perform multiple tasks that contribute to fitness.

36. The case two tasks The case of a trade-off between two tasks may explain the widespread occurrence of linear relations between traits. The Pareto Front

37. Pareto front geometry For three tasks, the Pareto front is the full triangle whose vertices are the three archetypes. In this case, because a triangle defines a plane, even high dimensional data on many traits are expected to collapse onto two dimensions. The closer a point is to one of the vertices of the triangle, the more important the corresponding task is to fitness in the organism’s habitat.

38. Evidence for triangular suites of variation in classic studies

39. Bacteria face a trade-off in partitioning the total amount of proteins they can make at a given moment between the different types of proteins, that is how much of each gene to express. Trade-off: rapid growth (ribosomes) vs. survival (stress response proteins) Beyond animal morphology Corr. of the top 200 temporally varying genes E.coli promoter activity Promoter activity of 3 genes at different time points

40. Thank you! Hope you enjoyed the course!!