Biological Algorithms Group

Our mission is to identify simple paradigms of robust motility control and pattern formation in complex biological systems. We reverse-engineer biological solutions of robust control in close collaboration with experimental biologists. We use tools from physics, information theory, and engineering; likewise, we seek to excite bio-inspired applications of biological information processing in these fields.

We focus on principles of biological information processing in two model systems:

  1. Motility control: We study how noisy sensory information controls biological motility and dynamic decision making, e.g. during sperm navigation to the egg.
  2. Pattern control: We study elementary rules of self-organized pattern formation during self-repair and adaptation, e.g. of load-balancing transport networks in the liver.

On top of that, we explore potential applications of biological control designs in advanced electronics applications in tight collaboration with the other paths of the cfaed.

We are currently searching for highly motivated and talented students to work at the interface of physics and biology with a twist towards computer science.

Group News




Nonlinear Dynamics and Stochastic Processes with Applications

Reader: Benjamin Friedrich

Time: Every Tuesday 16.40 (6.DS )

Room: PHY/B214 (Häckelstrasse 3 on main campus)




Nonlinear dynamical systems are studied in many fields of physics, engineering, electronics, and economics, including classical mechanics, biological physics and control theory. The theory of nonlinear dynamics provides a way of geometric thinking to identify dynamic steady states and oscillations in dynamical systems. It allows to assess the stability of these steady states and their behavior under change of control parameters, often without the need to solve dynamical equations explicitly.

This will be a first course in nonlinear dynamics, with a focus on geometric aspects and applications. Key theoretical concepts of dynamical systems theory will be introduced and illustrated by examples from physics, biology, and computer science. In a second part of the lecture, we will give an introduction to stochastic processes and study dynamics and robustness of nonlinear systems in the presence of noise.


Stability analysis, bifurcation theory, oscillators and synchronization, pattern formation, introduction to chaos, introduction to stochastic processes, Langevin and Fokker-Planck formalism, application to first passage time problems and Kramer’s escape rate theory.



Ordinary Differential Equations, Multi-variate calculus



  • Strogatz: Nonlinear Dynamics and Chaos, Westview, 2001 (gebraucht ab 20€)
  • Risken: The Fokker-Planck Equation, Springer, 1996
  • Stratonovich: Topics in the Theory of Random Noise, Martino, 2014
  • Ott: Chaos in Dynamical Systems, Cambridge University Press, 2002
  • VanKampen: Stochastic Processes in Physics and Chemistry, North-Holland, 2007