CloseHelpPrint
Kies de Nederlandse taal
Course module: UCSCIMAT22
UCSCIMAT22
Mathematical Modeling: Networks
Course info
Course codeUCSCIMAT22
EC7.5
Course goals
After completing this course students are able to:
  • understand and describe the importance of network theory, both in general and in a particular field of their interest
  • handle and apply basic graph theoretical concepts
  • apply network theory in mathematical modelling
Content

The interdisciplinary study of networks is recently receiving much attention. It is revealing unexpected connections between otherwise disparate fields such as sociology, ecology, economics, cognitive neuroscience, and computer science. Network thinking provides new ways to understand our strongly connected world. This approach has generated new tools for the analysis and understanding of complex systems in both the social and natural world.
The course will discuss how to describe and quantify networks, provide means to analyze network data (using among others graph theory) and explain how to build and analyze concrete mathematical models, e.g. of the spread of diseases or of financial crises.

 
Format
In addition to the contact hours, each student is expected to work nine hours a week on the course. This time should be devoted to: reviewing the material of the preceding and for the following lecture; finishing and preparing exercises (some to be handed in); reading research articles, writing a final essay, preparing for a presentation.
Math track
UCSCIMAT22 does not give access to UCSCIMAT31. Students wanting to complete a track in mathematical modeling are advised to do so with a suitable level-3 off-campus course.
For students wanting to complete a track in applied mathematics there are interesting level-3 Bachelor courses in social science (economic geography, sociology) and humanities (artificial intelligence, logic, linguistics) and also in science (e.g. in theoretical biology).
Here is a list of existing UU-courses which should be accessible upon completion of UCSCIMAT22:
- GEO3-3805, ECON-Organisational Networks, Matté Hartog (economic geography)
- 200700372, Social Networks (ECO). Dr. Gerard Mollenhorst (sociology)
- 200800018, MK: Social networks. Dr. Gerard Mollenhorst
- B-B3COMB10, Computational Biology, Prof. dr. Paulien Hogeweg
- KI3V12013, Logical Complexity, Dr. R. Iemhof

Master courses (no easy access but to indicate importance of networks):
- WBMV13005, Logic and Computation [Prof. Vincent van Oostrom]
- BMB508112, Bioinformatics in neuroscience [Prof. dr. R. Adan]
- WISM484 Introduction to complex systems (Prof. Dr. Jason Frank)
CloseHelpPrint
Kies de Nederlandse taal