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Statistics, Biophysics
Project Title Research Group
Statistical physics and genomics of bio-molecular networks

We study the interaction between genes, i.e., the building blocks of regulatory networks, in yeast, fruitfly, and human. We learn to use bioinformatics tools to extract the relevant information from genomes. We compare this information across species with nonequilibrium stochastic models to extract the evolution of regulatory networks.

Cellular automata modelling of interdisciplinary transport problems

Cellular automata can be applied to model different transport processes ranging from highway traffic and pedestrian dynamics to ant trails and intracellular transport of molecular motors. These models are variants of the Asymmetric Simple Exclusion Process, one of the fundamental and best-studied processes in nonequilibrium physics.

In this project a model for pedestrian dynamics will be studied by Monte Carlo simulations, supported by analytical arguments. The results will be compared with empirical data in order to calibrate and improve the model.

Modeling microbial evolution experiments

Experimental evolution with microbes such as bacteria or viruses studies how biological populations adapt to a new environment through mutations in the genetic code (genotype) that affect the ability of the organism to survive and reproduce (fitness). In this project we use simple mathematical models to account for the main features of such experiments, in particular the way the fitness and the number of acquired mutations increases with time.

Measurement of force generation by biological molecular motors

Molecular motors are the smallest complexes which can generate directed movement. Laser tweezers enable characterization of piconewton forces and nanometer displacements.  Therefore, they are ideal tools  for studying kinetics and force generation by molecular motors. The aim of the internship will be to get acquainted with laser tweezers and to use them for measuring the force generated by individual bacterial motors.