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Tutorial 12 Biological networks Biological networks • Protein-Protein interactions – STRING • Protein and genetic interactions – BioGRID • Network visualization – Cytoscape • Cool story of the day How to model natural selection Protein Protein interactions (PPI) http://string-db.org/ Protein Protein interactions (PPI) Protein Protein interactions (PPI) Protein Protein interactions (PPI) Protein Protein interactions (PPI) Protein Protein interactions (PPI) Protein Protein interactions (PPI) Will change according to the prediction method you choose. Protein Protein interactions (PPI) Protein Protein interactions (PPI) Protein Protein interactions (PPI) Protein and genetic interactions http://thebiogrid.org/ Protein and genetic interactions Protein and genetic interactions Protein and genetic interactions Signaling pathways Hearing and vision map Network visualization - Cytoscape http://www.cytoscape.org/ Network visualization - Cytoscape The input is a tab delimited file: <Protein 1> <interaction type> <Protein 2> Network visualization - Cytoscape Network visualization - Cytoscape Network visualization - Cytoscape Network visualization - Cytoscape Network visualization - Cytoscape Degree: the number of edges that a node has. The node with the highest degree in the graph Network visualization - Cytoscape Closeness: measure how close a node to all other nodes in the network. The nodes with the highest closeness Network visualization - Cytoscape Betweenness: quantify the number of all shortest paths that pass through a node. The node with the highest betweenness Network visualization - Cytoscape Know your network type: Directed – for regulatory networks Undirected – for protein-protein networks Network visualization - Cytoscape (Analysis of another network) Network visualization - Cytoscape Highest degree = big Highest betweens = red Network visualization - Cytoscape Cytoscape has ~200 plugins http://chianti.ucsd.edu/cyto_web/plugins/ Cool Story of the day How to model natural selection 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. The Pareto Front The case two tasks The case of a trade-off between two tasks may explain the widespread occurrence of linear relations between traits. 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. Evidence for triangular suites of variation in classic studies Beyond animal morphology 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) E.coli promoter activity Corr. of the top 200 temporally varying genes Promoter activity of 3 genes at different time points Thank you! Hope you enjoyed the course!!