BCB 715 Modeling Signaling Pathways
Instructor: Tim Elston (email@example.com or 843-7670)
The course will provide an introduction to the basic mathematical techniques used to develop and analyze models of signaling pathways and regulatory networks. Both deterministic and stochastic models will be discussed. The numerical techniques covered in the class will include methods for solving ordinary differential equations and Monte Carlo methods. If time permits, the diffusion equation also will be considered. Homework assignments will be completed using MATLAB. No experience using MATLAB is assumed. Particular emphasis will be placed on feedback and feed-forward control mechanism used to regulate biochemical pathways. The course will be self-contained, with all the necessary biology and mathematics covered in class. However, students are expected to have taken undergraduate calculus.
- Mastering MATLAB7. D Hanselman and B. Littlefield, Prentice Hall (2004)
- Computational Cell Biology. Editors C. Fall, E. Marland, J. Wagner, and J.Tyson, Springer Verlag (2002)
- Nonlinear Dynamics and Chaos. S. Strogatz, Wesview Press (1994).
- An Introduction to Systems Biology: Design Principles of Biological Circuits. Uri Alon, Chapman and Hall/CRC (2006).
*The course will use the Blackboard system as the primary mode of communication: http://blackboard.unc.edu
- The logistic map and MATLAB
- Simple regulatory motifs and ordinary differential equations
- Chemical kinetic equations with applications to Michaelis-Menten kinetics and cooperativity
- Feedback control mechanisms, signal-response curves, and oscillations
- Introduction to stochastic processes and diffusion
- Stochastic Modeling with applications to gene regulation
- Diffusion and spatial models