MAE 298, Spring 2009 (CRN: 79691)
Advanced Topics in Network Theory
Computer NetworksBiological NetworksTransporation Networks
Instructor: Prof. Raissa D'Souza
Email: raissa at cse.ucdavis.edu
Office: 1101 Mathematical Science Building
Teaching Dr. Elizabeth Leicht
Assistant: Email: eleicht at ucdavis.edu
Office: 1228 Mathematical Science Building
Lectures: Tues & Thurs 2:10-4:00pm, 1128 Hart
Class Schedule










Overview:
Network structures are pervasive in the world around us, from the Internet and the power grid, to social acquaintance networks, to biological networks. In the past decade a science of networks has begun to emerge, blending techniques and research from physics, computer science, biology and the social sciences. This will be a seminar course exploring recent advances in network theory and specialized topics of interest to enrolled students. Enrolled students will ideally be using networks of some form in their research and should have familiarity with basic network theory, such as covered in the review article: "The Structure and Function of Complex Networks", M. E. J. Newman, SIAM Review 45 (2), 167-256, 2003. Other Prerequisites: familiarity with linear algebra, basic statistics, calculus, ordinary differential equations.

Course structure/Expectations (Details here):
1) Read 2 to 4 research papers per week.
2) Attend all classes and participate vigorously in discussion.
3) Prepare and lead classroom discussions on two topics.
4) Prepare a moderate-length survey paper on these topics.

Potential topics (More topics here):
-- Design of transportation/distribution networks/energy networks
-- Biological networks: Genetic regulation, microarray data, protein interactions
-- Social networks: Community structure, influence, consensus building, survey data
-- Software networks: Function call graphs, developer communication, socio-technical congruence
-- Immunology/epidemiology/computer viruses
-- Resilience principles for networks
-- Visualization software
-- Graph theory, random graphs, new network metrics
-- Preferential attachment, optimization, Internet growth and modeling
-- WWW crawling and searching
-- Dynamic networks, self-organization and sensor networks

Resources: There will be no required text for this course. The content will largely come from articles. Several technical texts, covering aspects of network theory, are available and might be worth purchasing.

Some useful references:

  • Network Theory with Applications. An introductory course on network science.

  • The Structure and Function of Complex Networks, by M. E. J. Newman, SIAM Review 45 (2), 167-256, 2003.

  • Random Graph Dynamics, by Rick Durrett.

    • A Recent review highlighting the differences of network analysis in the social versus physical sciences:
  • Network Analysis in the Social SciencesS. P. Borgatti, A. Mehra, D. J. Brass, G. Labianca, Science 323, 892-895, 2009.