Modeling and Simulation
This course teaches modeling techniques for spatially resolved biological systems. You will learn to model and simulate biological systems and to develop and implement the corresponding algorithms. After repetition of the basics from mathematics and physics, you will model processes such as diffusion and flow, and simulate them in the computer using your own codes and the numerical framework of particle methods.
Contents
dimensionality analysis, causality diagrams, vector fields, particle methods, governing equations for diffusion and flow, hybrid particlemesh methods for computer simulations, student project: simulation of a biological system.
Time/Place
Lecture: Tuesdays, 4. DS (13:0014:30), APB2026 (AndreasPfitzmannBau) / FIRST LECTURE: APR 5
Exercises: Thursdays, 4. DS (13:0014:30), MPICBG (Pfotenhauerstr. 108) / FIRST TUTORIAL: APR 21
Teachers
Lecture: Prof. Ivo F. Sbalzarini
Exercises: Dr. Michael Hecht, Pietro Incardona, Anastasia Solomatina
Learning goals

Analysis of the dynamic behavior of biological systems with spatial structure

Formulation of a model of the system behavior

Computer simulation of the model using particle methods
We focus on biological systems. The taught methods and concepts are, however, applicable in a much broader sense.
Lecture language: ENGLISH
Please find below the lecture syllabus, the slides, the selfcheck questions, and the exercises:
 Lecture 1  Administration and Introduction
 Lecture 2  Dimensional Analysis
 Lecture 3  Modeling Dynamics: Reservoirs and Flows
 Lecture 4  Recap on Vector Analysis
 Lecture 5  Conservation Laws and Control Volume Methods
 Lecture 6  Particle Methods
 Lecture 7  Diffusion
 Lecture 8  ReactionDiffusion
 Lecture 9  AdvectionDiffusion
 Lecture 10  Flow
 Lecture 11  PDEs
Full lecture notes will be provided to the students of the course.
Project
The student project will aim at implementing the Quorum Sensing model proposed by J. Müller et al. as described here.