|
SGN-6186 Mathematical Modeling of Cellular Systems, 5 cr |
Tiina Manninen
Lecture times and places | Target group recommended to | |
Implementation 1 |
|
DI-Opiskelijat
International Students Jatko-opiskelijat Kandiopiskelijat |
Final examination, weekly exercises, and an assignment.
Completion parts must belong to the same implementation
After completing the course, the student will be able to create mathematical models, both deterministic and stochastic, of cellular systems, implement them, and solve their behavior computationally by running simulations. Systems include signal transduction, metabolism, and single cells. Morover, the student is able to explain the differences between deterministic and stochastic methods. After the course, the student has the necessary skills to use MATLAB environment in modeling.
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Biological background of different cellular systems. | ||
2. | Deterministic and stochastic methods to model the dynamical behavior of cellular systems. | ||
3. | Simulation of deterministic and stochastic models. |
The final grade comes from the exam. The grade is incremented by one if weekly exercises and assignment are done.
Numerical evaluation scale (1-5) will be used on the course
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Lecture slides | Mathematical Modeling of Cellular Systems | Tiina Manninen | English | ||||
Research | Scientific articles | English |
Course | Mandatory/Advisable | Description |
SGN-6106 Computational Systems Biology | Mandatory |
There is no equivalence with any other courses
Course will be lectured every other year. Course will be lectured in the academic year 2009-2010. The credits of this course can be used for replacing SGN-6156 Computational Systems Biology II.
Description | Methods of instruction | Implementation | |
Implementation 1 | Student will learn how to create mathematical models, both deterministic and stochastic, of cellular systems and solve their behavior computationally by running simulations. Systems include signal transduction, metabolism, and single cells. | Lectures Excercises |
Contact teaching: 35 % Distance learning: 0 % Self-directed learning: 65 % |