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Theory of Biological Networks

Prof. Karen Alim

Research Field

Life is mesmerizing. How does shape and structure emerge when organism grow? We want to identify the physics that are underlying the morphing of life. Physical forces are eminent for pushing and squeezing living matter as it morphs into life. Observing the physical forces that arise from cell mechanics or fluid flows is key to understand how these physical forces generate and transport information - information that is read out by living matter and feeds back onto its dynamics but also its physical properties itself, thus morphing structures, organs and organisms. To succeed we combine quantitative observation of life with theoretical models to finally capture the key processes in simple mathematical terms. Here, it is important to choose experimental model systems that are particularly good for observation and quantification but also provide an accessible level of abstraction for theory. That is why we work with the slime mould Physarum polycephalum and at the same time built in vitro model systems in the lab. Theoretical models developed both with pen and paper and simulations in the group both inspire experiments and explain observations. Life still hides many fundamental processes that once uncovered can revolutionize our designs, engineering or medical treatment.


James-Franck-Str. 1/I
85748 Garching b. München

Members of the Research Group





Other Staff


Course with Participations of Group Members

Titel und Modulzuordnung
Fortgeschrittene statistische Physik
Zuordnung zu Modulen:
VO 4 Alim, K. Di, 08:00–10:00, PH 1121
Fr, 10:00–12:00, PH 1121
Aktuelle Entwicklungen zur Physik biologischer Netzwerke
Zuordnung zu Modulen:
PS 2 Alim, K. Mi, 10:00–12:00, CPA EG.006B
Mi, 10:00–12:00, CPA EG.006B
sowie einzelne oder verschobene Termine
Exercise to Continuum Mechanics
Zuordnung zu Modulen:
UE 2 Burger, L. Kienlein, M. Mirzapour, F. Quoika, P. Sustay Martinez, C. … (insgesamt 6)
Leitung/Koordination: Zacharias, M.
Übung zu Fortgeschrittene statistische Physik
Zuordnung zu Modulen:
UE 2
Leitung/Koordination: Alim, K.
Journal Club Biological Physics and Morphogenesis
Zuordnung zu Modulen:
SE 2 Alim, K. Do, 13:00–15:00, CPA EG.006B
sowie einzelne oder verschobene Termine
Repetitorium zu Aktuelle Entwicklungen zur Physik biologischer Netzwerke
Zuordnung zu Modulen:
RE 2
Leitung/Koordination: Alim, K.
Tag der Physikerinnen
aktuelle Informationen
Zuordnung zu Modulen:
KO 0.1 Alim, K. einzelne oder verschobene Termine
Tutorenseminar zu Fortgeschrittene statistische Physik
Diese Lehrveranstaltung ist keinem Modul zugeordnet.
SE 2 Alim, K.

Offers for Theses in the Group

Active response by adaptation of mechanical properties?

The complex behavior of the giant cell Physarum polycephalum finds its origin in the versatile transformation of liquid cytoplasm to gel-like actin-myosin meshwork making up the tube walls and vice versa. These active mechanics allow the organism to recycle its’ gel-like tubes at its rear and move it in its fluid form to the front, where it grows. Also, responding to stimuli like food, touch, or light, a change in cytoplasm viscosity seems to initiate the response. Yet, what are the mechanical properties of the liquid cytoplasm, and how much do they change upon stimulation? Do the mechanical properties of the cytoplasm change with the location in the cell? The measure of the mechanical properties of cells is challenging, but one can probe their visco-elasticity by tracking injected micron-sized beads - a technique called microrheology. You will measure the mechanical properties of cytoplasm extracts and grown Physarum, and quantify how they change upon stimulation by passive and active microrheology. Task 1: Establish cytoplasm extraction following previous work in the literature. Task 2: Perform passive microrheology on cytoplasmic droplets without and with stimulation (light, food, drugs) and analyze your data quantitatively. Task 3: Establish active microrheology to extract cytoplasm viscosity in different parts of Physarum’s network.

suitable as
  • Bachelor’s Thesis Physics
Supervisor: Karen Alim
Mapping network theory to network function
Networks exist as our social network, the world wide web, traffic routes but also as flow networks making up the vasculature of animals, plants, fungi and slime moulds. While a lot of measures have been developed to describe networks in general it is not clear how these measures are predicting network function via network architecture. You will quantify physical networks of the slime mould and numerically generated model networks with network theoretic measures. Mapping to slime mould behaviour and model network flow and transport function will allow you to identify predictive network theoretic measures. You will learn network theory, Matlab. Prerequisites: statistical physics. Task 1 Collect network theoretic measures from the literature and Matlab packages Task 2 Apply network theoretic measures on slime mould and model data and map their property onto the network architecture Task 3 Correlate link by link network theoretic measure and flow/transport in the link under inspection to identify measures of predictive power.
suitable as
  • Bachelor’s Thesis Physics
Supervisor: Karen Alim

Current and Finished Theses in the Group

The effect of aversive external conditions on the migration of small plasmodia of Physarum polycephalum
Abschlussarbeit im Masterstudiengang Physik (Biophysik)
Themensteller(in): Karen Alim
Investigating metabolic changes in genetically modified stem cell-derived beta cells.
Abschlussarbeit im Masterstudiengang Biomedical Engineering and Medical Physics
Themensteller(in): Karen Alim
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