Instructor: Prof. Dr. Verena Wolf
Assistant: Alexander Andreychenko
News:
 Grades for final exam. Inspection: 20 February, 14:3016:30 (other dates/times will be announced later)
 We offer a follow up seminar in the summer term (link).
 Since we had twice as many lectures before the midterm compared to the number of lectures after the midterm, we will compute the final grade as 2/3*grade of midterm + 1/3*grade of final.
 An oral reexam about the whole material is possible (but the grade of the written exams then become obsolete).
Schedule: Tuesday 12:15 – 13.45, Building E2 1 – Room 007
Tutorial slots:
Thursday 12:1513:45 (BioInf, SR001)
Credits: 6 ECTS points
Course Material:
 lecture notes (Feb 4th, 2014)
 Exercise sheet 1 (see lecture notes for the solution)
 Exercise sheet 2 (solution sketch)
 Exercise sheet 3 (solution sketch)
 Exersice sheet 4 (mockup for the programming exercise, matlab solution sketch, theoretical exercises solution sketch)
 Exercise sheet 5 (mockup for the programming exercise, matlab solution sketch, theoretical exercises solution sketch)
 Exercise sheet 6 (Matlab Code Gillespie Simulation for gene expression example, theoretical exercises solution sketch, fixed solution sketch)
 Exercise sheet 7 (solution sketch )
 sample questions to prepare for midterm exam (mockup exam task, version with solutions)
 Exercise sheet 8 (model xml file, remark about StochKit usage, solution sketch, changed model xml)
 Exercise sheet 9 (solution sketch, resource for Task 3)
 Exercise sheet 10 (matlab mockup, matlab example solution, solution sketch)
 Exercise sheet 11 (solution sketch, task 1 solution fixed)
 sample questions to prepare for final exam (mockup exam task, solution sketch)
 preparation for Tuesday 22.10: video playlist
 preparation for Tuesday 29.10: video playlist
 preparation for Tuesday 05.11: video playlist
 preparation for Tuesday 12.11: video playlist
 preparation for Tuesday 19.11: video playlist
 preparation for Tuesday 26.11: video playlist
 preparation for Tuesday 03.12: video playlist
 preparation for Tuesday 10.12: video playlist
 preparation for Tuesday 07.01.14: video playlist
 preparation for Tuesday 14.01.14: video playlist
 preparation for Tuesday 21.01.14: video playlist
 preparation for Tuesday 28.01.14: video playlist
Objectives:
The course aims at giving the participants knowledge of methods, techniques, and concepts in the study of dynamical models that arise in the area of systems biology. The main focus of the course is on the mathematical analysis of intrinsically stochastic processes in the cell (e.g. gene expression). This course is a flipped classroom course which means that exercises are solved/presented during the two slots and the homework consists in watching videos which will be uploaded at the course homepage.
Prerequisites:
The course is open to students from computer science or bioinformatics interested in stochastic modelling and systems biology. The course does not require previous experience in biology. Mathematical skills as well as basic programming skills are of advantage but not mandatory.
Certification Conditions:
There will be two written exams. Their grades contribute with 2/3 (midterm) and 1/3 (final) to the final grade (“Schein”). The assignments are optional but bonus points may be obtained during the tutorial. An oral reexam is possible.
Exam Schedule: Midterm exam: Dec 17, 12:15 – 13:25 Building E1 3 – HS 003 (results)
final exam: Feb 11, 12:15 – 13:15 Building E1 3 – HS 001
Using Matlab:
As a part of the assignments the participants will have to program in Matlab. Instructions on how to get access to Matlab.
Syllabus:
 PART I – OVERVIEW
 Reaction Rate Equations
 Why Stochastic Models?
 Basic concepts of probability
 Stochastic chemical kinetics
 PART II – STOCHASTIC SIMULATION
 Simulation algorithms
 Basic concepts of statistics
 Statistical output analysis
 PART III – NUMERICAL APPROXIMATION ALGORITHMS
 Direct Approaches
 Moment Closure Approaches
 Hybrid Approaches
 PART IV – PARAMETER ESTIMATION
 Maximum Likelihood Estimation
 Bayesian Inference
Text Books:
 Stochastic Modelling for Systems Biology. Darren J. Wilkinson, Crc. Pr. Inc, 2006.
 Simulation Modelling and Analysis. Averill M. Law, McgrawHill, 2006.
 Introduction to the Numerical Solution of Markov Chains. William J. Stewart, Princeton Univ. Pr., 1994.
 Systems Biology: Dynamic Pathway Modelling. O. Wolkenhauer.
 INTRODUCTION TO PROBABILITY. C. Grinstead and L. Snell
