IDC407: Network science

        [Cr:4, Lc:3, Tt:1, Lb:0]

Course Outline

• Introduction and history of networks: Pervasiveness of networks in nature and everyday life, Surprising powers of networks, Bucket chain, MafiaBoy, Euler’s theorems, Strong and weak ties: Granovetter, Six degree of separation: Stanely Milgram.
• Network data: Social networks, World Wide Web and Internet, Wikipedia and Facebook networks, highway and flight networks, power grids, biological networks, ecological networks, economics networks, dark networks, disease networks, happiness networks etc.
• Structure of networks: Network attributes, vertex, edge, weak links, date/party links , components, Planar/nonplanar, cyclic/noncyclic, directed/undirected, weighted graphs, trees, Random model of networks: Erdos-Renyii, Small world property of networks, Scale-free networks and their importance in robustness of systems, Hierarchical networks and clustering coefficient, Network motif, modules, overlapping modules and their relevance, Network centralities: degree, betweenness, closeness, Eigen vector centrality, and community centrality, Centrality-lethality paradigm and the conflicts in biological context, Different topologies of networks: Assortativity, dis-assortativity, Rich-club phenomenon, Networks of networks, Coupled and interdependent networks.
• Dynamics of networks: Preferential attachment model, Network percolation, Information flow in the networks, Perturbation and error propagation in networks, Epidemic models, Synchronization of networks, Controllability of networks.
• Statistical analyses of networks: Mapping networks, Network data structures: adjacency matrix, hash of hash/arrays etc, Sampling networks for control analyses, Quantifying network, node and edge attributes, Graph traversal, Graph partitioning, Identification and scoring of network modules, Quantifying group evolution, Modeling network dynamics, Modeling gene regulatory networks, Reconstructing networks from multi-dimensional datasets (like microarray), Network visualization and analysis software: Cytoscape, Pajek, Osprey etc.
• Research paper discussion: Key papers across disciplines will be discussed.

Recommended Reading

•  Barabási, Albert-László. Linked: The New Science of Networks. Perseus Books Group. ISBN 9780738206677.
• M. E. J. Newman (2010). Networks: An Introduction. Oxford: Oxford University Press.  ISBN 0-19-920665-1.
• Csermely, P. (2006, re-print: 2007, 2nd paperback edition: 2009) Weak links: Stabilizers of Complex Systems from Proteins to Social Networks, Springer Verlag, pp. 392, see the downloadable chapters here: 
  www.weaklink.sote.hu/weakbook.html.
  The Google version of the book:
  http://books.google.com/books?id=bu34G3A2E9YC