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Prof. Dr. rer. nat. Ulrich Gerland

Photo von Prof. Dr. Ulrich Gerland
+49 89 289-12394
PH: 3333
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Theory of Complex Bio-Systems
Job Titles
  • Department Council Member: Representative of the professors
  • Professorship on Theory of Complex Bio-Systems
Consultation Hour
on appointment

Courses and Dates

Title and Module Assignment
Computational Methods for Molecular Evolution
current information
Assigned to modules:
VO 2 Braun, D. Frey, E. Gerland, U. Thu, 14:00–16:00, virtuell
Theory of Stochastic Processes
eLearning course
Assigned to modules:
VO 4 Gerland, U. Mon, 08:30–10:00, virtuell
Wed, 12:00–14:00, virtuell
Current Topics in Theory of Complex Bio-Systems
Assigned to modules:
HS 2 Gerland, U. Wed, 10:00–12:00, PH 3343
Exercise to Theory of Stochastic Processes
Assigned to modules:
UE 2
Responsible/Coordination: Gerland, U.
dates in groups
Biomolecular Systems
Assigned to modules:
SE 2 Gerland, U. Simmel, F. Zacharias, M. Thu, 12:00–13:30, virtuell
Revision Course to Current Topics in Theory of Complex Bio-Systems
Assigned to modules:
RE 2
Responsible/Coordination: Gerland, U.
Seminar for Tutors in Theory of Stochastic Processes
This course is not assigned to a module.
SE 2 Gerland, U.

Offered Bachelor’s or Master’s Theses Topics

Growing shapes: Kinetics of integrating cell wall material into the envelope of a growing cell

The aim of this Master thesis is to explore different modes of cell wall growth, which is locally controlled by enzymes but has a global effect on the shape of the cell. Which schemes of enzymatic action permit stably growing cell shapes? And which ones can mimick the observed growth behavior of different bacterial species? These fundamental questions are surpisingly largely open, partially due to the difficulty of experimentally determining which local properties of the cell wall affect the enzymatic activity. In light of this experimental barrier, conceptual theoretical models can classify different plausible schemes by their large-scale behavior, which is more easily observed experimentally. This thesis will combine simulations of stochastic models for growing shapes with simple analytical toy models to address some of the open questions.

suitable as
  • Master’s Thesis Biophysics
  • Master’s Thesis Theoretical and Mathematical Physics
Supervisor: Ulrich Gerland
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