Course Coordinator: 
Hiroaki Kitano
Igor Goryanin
Computational and Mathematical Biology

Computational approaches to science in general, and particularly in biology, are an increasingly important topic. However, understanding the concepts behind such computational approaches in biology is particularly difficult due to discrepancies in the methodologies and languages that are used. This course covers basics of computational and mathematical biology with strong emphasis on understanding of computational foundation and practical modeling of metabolic networks and signal transduction networks. Students are expected to actively participate in hands-on modeling sessions. A series of numerical computation, statistical, and intelligent systems approaches will be shown in the context of computational biology. The course will introduce standards used in the field such as SBML, SBGN, BioPAX, and MIRIAM, and students will gain direct experience in modeling sessions using CellDesigner (http://www.celldesigner.org/) PhysioDesigner (http://www.physiodesigner.org/).

Course Dates 2014: Intensive 3-week course, 4-20 August 2013 (Minimum 2 hours class time per day plus reading and exercises)

The goal of this course is to provide basic exposure to computational and mathematical thinking about basic biological processes and learn how to construct models and analyze them for biological studies.
Course Content: 


  1. Course Overview and Introduction of Computational Biology (Kitano)
  2. Computational Foundation of Metabolomics (Goryanin)
  3. Metabolic network reconstruction (Goryanin)
  4. Metabolic network modeling (Goryanin)
  5. Mark up languages: SBML, SBGN (Goryanin)
  6. Metabolic Database resources and development (Goryanin)
  7. Metabolic Modeling and Practical applications (Goryanin)
  8. Metabolic Pathways Reconstruction and Modeling: Practical Session (Goryanin)
  9. Metabolic Pathways Reconstruction and Modeling: Practical Session (Goryanin)
  10. Signal Transduction & Metabolic Modeling: Practical Session (Kitano & Groyanin)
  11. Signal Transduction Modeling: Practical Session (Kitano)
  12. Computational Foundation of Signaling (Kitano)
  13. Computational Foundation of Cell Cycle (Kitano)
  14. Practical applications of signal transduction modeling (Kitano)
  15. Advanced topics in computational biology (Kitano)
Course Type: 
Written report, 50%; Project, 50%.
Text Book: 
Systems Biology: A Textbook by Klipp, Liebermeister, Wierling, Kowald, Lehrach, and Herwig (2009)
An Introduction to Systems Biology: Design Principles of Biological Circuits, by Uri Alon (2006)
Kinetic Modelling in Systems Biology, by Oleg Demin and Igor Goryanin (2008)
Prior Knowledge: 

Requires at least advanced undergraduate level Cell Biology and Genetics or similar background knowledge, plus B22 Computational Methods or similar coding experience.