BMT-52406 Models of Gene Networks, 3 cr

Implementation BMT-52406 2018-01

Description

From this course the student will know how to do exact stochastic simulations, delayed stochastic simulations, and how to create models of delayed stochastic gene regulatory networks. Students will become familiar with detailed models and experimental results related to single gene expression and its underlying mechanisms. Also, the student will be introduced to basic concepts of cell type and cell differentiation and learn the latest modeling techniques in these topics.

Lessons

Assessment scale

Numerical evaluation scale (0-5)

Requirements

a) Exercises (Must complete at least 50% of exercise points. 80% provides a bonus of 0.5 out of 5).
b) Final exam (50% of the final grade).
c) Project work (50% of the final grade).
d) Short summary (1-5 lines) of the lecture at the end of each lecture (in at least 4 lectures to be eligible to get bonus). The grade of each summary is: PASS/FAIL. If 3 or 4 summaries have PASS grade, the student gets a bonus of 0.5 in the final grade.

Additionally, a passing grade must be achieved in project, exam, and exercises.

Grading: 0 to 5 (0 fails, 1 to 5 passes). 2.5 from exam, 2.5 from project, 0.5 bonus for good performance in exercises, and 0.5 bonus for good performance lecture summaries.

Additional information of course implementation

http://www.cs.tut.fi/%7Esanchesr/BMT-52406/index.htm