de | en

Prof. Dr. rer. nat. Karen Alim

Photo von Prof. Dr. rer. nat. Karen Alim.
Phone
+49 89 289-12192
Room
EG.036
E-Mail
k.alim@tum.de
frauenbeauftragte@ph.tum.de (Equal Opportunity Officer of the Physics Department)
Links
Homepage
Page in TUMonline
Group
Theory of Biological Networks
Job Titles

Courses and Dates

Title and Module Assignment
ArtSWSLecturer(s)Dates
From Biofluids to Bionic
eLearning course
Assigned to modules:
VO 2 Alim, K. Mon, 14:00–16:00, CPA EG.006A
Physics & Life
Assigned to modules:
HS 2 Alim, K. singular or moved dates
Seminar to From Biofluids to Bionic
Assigned to modules:
HS 2 Alim, K.
Current Developments in Physics of Biological Networks
Assigned to modules:
SE 2 Alim, K. Wed, 10:00–12:00, virtuell
Mentoring in the Bachelor’s Program Physics
Assigned to modules:
KO 0.2 Alim, K. dates in groups
Revision Course to Physics & Life
Assigned to modules:
RE 2
Responsible/Coordination: Alim, K.
Revision Course to Seminar to From Biofluids to Bionic
Assigned to modules:
RE 2
Responsible/Coordination: Alim, K.

Offered Bachelor’s or Master’s Theses Topics

Cooking up life in the white smoker
White smokers are likely the cradle of life. Their caves and tunnels allow reactants to accumulate at catalytic sites to start the reactions at the origin of life. How do these catalytic sites form and grow with the smoker? You will grow two-dimensional smokers on a microfluidic chip and measure the smoker geometry from your data. You will learn about microfluidics, microscopy, Matlab, image analysis and the fluid physics of laminar flow in flow networks. Prerequisites: Statistical physics and fascination for the wonders of nature. Task 1 Learn and improve the experimental setup to control the microfluidic device for smoker formation Task 2 Experimentally explore the morphologies of smokers as you vary inflow rate and inlet geometry Task 3 Quantify smoker morphology with respect to the flow network geometry within the smoker. Built a hypothesis which physical conditions favor the formation of caves as catalytic sites.
suitable as
  • Master’s Thesis Biophysics
Supervisor: Karen Alim
Dynamic patterns of plant development
Plants mainly develop all their organs like leafs and flowers continuously at their stem. How can the patterning underlying the positioning of these organs at the plant shoot be so robust? You will investigate with numerical simulations the patterning at the tip of the plant shoot and study how variations in cell size and cell number at the shoot impact patterning. You will learn python, pattern formation, mechanics. Prerequisites: Enjoy programming Task 1 Generate different cell geometries on a spherical shell by getting to know our plant simulation code Task 2 Run our pattern formation simulation on the cells and program measures that characterize the patterns you observe Task 3 Quantify how cell geometry impacts pattern formation
suitable as
  • Bachelor’s Thesis Physics
Supervisor: Karen Alim
How our veins adapt
Our vein network is important for transporting oxygen and other important resources in our body. Our vein network is not static but continuously adapts its structure and the thickness of individual veins. What laws govern the dynamics of individual veins? What role does the flow in the cores play? You will analyse data from vein networks on a microfluidic chip in order to quantitatively record the dynamics of the veins. For this purpose, you will further develop image analysis methods and adapt them to our completely new data of veins. Task 1 Learn how to work with the machine-learning based image analysis tool ilastik Task 2 Quantify vein diameters and vein network morphologies from existing vein microfluidic data
suitable as
  • Master’s Thesis Applied and Engineering Physics
Supervisor: Karen Alim
In vitro and in silico assessment of the microvascular network under fluid flow
Blood vessels deliver oxygen and necessary nutrients to all tissues in the body. During embryonic development, formation of the first primitive vascular labyrinth though vasculogenesis is followed by vascular network expansion and maturation through angiogenesis. The latter comprises formation of new blood vessels out of pre-existing ones and the subsequent vascular remodeling in order to adapt the vascular network to the specific metabolic demands of the surrounding tissue. Onset of blood flow into the primary vascular network is known for having major impacts on vascular remodeling ensuring the network’s efficiency through structural normalization and hierarchy. Owing to the fact that vessel remodeling is often found impaired in pathological angiogenesis, many therapeutic methods have been developed to interfere with the vessel growth and normalization strictly affecting vascular morphology. However, the exact correlation between vessel morphological variations and alterations in blood flow dynamics has not been fully elucidated. Moreover, while many animal models have been developed to assess the effect of blood fluid flow on vascular morphology, translating their outcomes to human vascular system is often challenging. Employing the recent state-of-the-art microfluidic techniques for human organ-on-a-chip developments, one can grow perfusable human capillaries on polymeric chips for direct investigation of vascular structural development under flow through real time observations. Taking advantage of our in-house established human microvasculature on PDMS chip models, this project is aimed to assess the impact of fluid flow on the microvascular network architecture and vessel caliber. To this end you will be working with existing 2D network image datasets analysing the microvascular structural remodeling in response to the fluid flow.
suitable as
  • Master’s Thesis Biomedical Engineering and Medical Physics
Supervisor: Karen Alim
Self-Organizing flow networks
Flow transport in complex networks is abundant in biology and engineering, from the vasculature of animals, to the hyphal networks of fungi, to the random networks making up batteries. Living systems continuously adapt their network morphology in response to stimuli; local feedback leads to self-organized structures optimal for fluid transport. In contrast, transport through engineered random networks is inefficient being limited to a few fast lanes. The current strategy to optimize flows in engineering is to build, branch by branch, an optimized network morphology. Here, we will lay the foundation for an entirely new bio-inspired approach namely to self-organize networks for optimal transport by local feedback. You will develop theoretical models to design feedback between chemical stimuli and network morphology that optimize for transport. The core idea is to optimize for transport by evening out flows as the network morphology is changed in response to a chemical transported by the flows pervading the network itself. Task 1 At first you will focus on simple network motifs as a Y-shaped and H-shaped structure. Solving theoretically for transport and absorption of chemical reagents in these network motifs will allow to deduce the physical parameters that allow to optimize transport in these network motifs. Task 2 You will then test your analytical predictions within a simulation of adaptive flow networks.
suitable as
  • Master’s Thesis Theoretical and Mathematical Physics
Supervisor: Karen Alim
Storing memories in vascular architecture
Arteries making up our vasculature are dynamics and continuously change their diameters in response to the flows pervading them. In fact, those changes allow the vasculature to store memories about flows in the past. Yet, on which time scales are memories made and forgotten? You will numerically simulate memory formation in a model of adaptive networks. Numerically probing for memories at different time intervals you will determine the physical parameters that govern how long it takes to form a memory and when memories are forgotten. You will learn about statistical physics of disordered systems, Matlab. Prerequisite: Good memory :) Task 1 Implement local artery dynamics into our Matlab code Task 2 Numerically write and probe memory formation while varying model parameters Task 3 Derive scaling relation on how model parameters determine the time scales of memory formation and loss.
suitable as
  • Bachelor’s Thesis Physics
Supervisor: Karen Alim
Strukturen für den Ursprung des Lebens

Weiße Raucher sind wahrscheinlich die Wiege des Lebens. Ihre Höhlen und Tunnel ermöglichen es Reaktanten an katalytischen Stellen anzusammeln, um damit die Reaktionen am Ursprung des Lebens in Gang setzen. Wie entstehen und wachsen diese katalytischen Stellen mit dem Smoker? Sie werden zweidimensionalen Smoker auf einem Mikrofluidik-Chip wachsen lassen und aus Ihren Daten die Rauchergeometrie vermessen und damit Strömung und Transport im Netzwerk berechnen und mit Ihren Daten vergleichen. Sie lernen Mikrofluidik, Mikroskopie, Matlab, Bildanalyse und die Strömungsphysik der laminaren Strömung in Strömungsnetzen kennen. Voraussetzungen: Statistische Physik und Faszination für die Wunder der Natur.

suitable as
  • Master’s Thesis Applied and Engineering Physics
Supervisor: Karen Alim
Vasculature remodeling following a ‘stroke’
Our vasculature forms redundant connections to robustly provide supply via the stream pervading our vasculature. Yet, vessel occlusions, strokes, threaten the steady supply by interrupting transport. Which network geometry poses a vasculature at risk in the event of a stroke? You will quantify network dynamics in existing data of both or network model organism Physarum polycephalum and human vasculature culture on a chip. Mathematically estimating the importance of individual veins within observed networks will guide you to identify which network geometries pose risks. You will learn about fluid flows in networks, Matlab. Prerequisites: Electrodynamics Task 1 Learn how to calculate resistances and network equivalent resistances in flow networks Task 2 Quantify vein resistances in different experimental data of vasculature. Preliminary code is provided. Task 3 Compare your predictions to real data of vasculature remodelling. Built a hypothesis which network geometries are at risk. Calculations of network resistances on small model networks may help you here.
suitable as
  • Master’s Thesis Biophysics
Supervisor: Karen Alim
Wie Adern wachsen und sich anpassen
Unser Adernetzwerk ist wichtig um Sauerstoff und andere wichtige Ressourcen in unserem Körper zu transportieren. Dabei ist unser Adernetzwerk nicht statisch sonder passt sich in seiner Struktur, in der Dicke einzelner Adern fortwährend an. Welche Gesetzmäßigkeiten folgt die Dynamik einzelner Adern? Welche Rolle spielt dabei die Strömung in den Adern? Du wirst Daten von Adernetzwerken auf einem Mikrofluidik Chip analysieren, um die Dynamik der Adern quantitativ zu erfassen. Dazu entwickelst Du Bildanalyseverfahren weiter und passt sich auf unsere ganz neuen Daten von Adern an.
suitable as
  • Bachelor’s Thesis Physics
Supervisor: Karen Alim

Publications

Changing flows balance nutrient absorption and bacterial growth along the gut
Agnese Codutti (author), Jonas Cremer (author), Karen Alim (author)
2022-02-18
other
DOI: 10.1101/2022.02.16.480685
Network architecture determines vein fate during spontaneous reorganization, with a time delay
Sophie Marbach (author), Noah Ziethen (author), Leonie Bastin (author), Felix K. Bäuerle (author), Karen Alim (author)
2021-12-30
other
DOI: 10.1101/2021.12.29.474405
Nuclei are mobile processors enabling specialization in a gigantic single-celled syncytium
Tobias Gerber (author), Cristina Loureiro (author), Nico Schramma (author), Siyu Chen (author), Akanksha Jain (author), Anne Weber (author), Anne Weigert (author), Malgorzata Santel (author), Karen Alim (author), Barbara Treutlein (author), J. Gray Camp (author)
2021-04-30
other
DOI: 10.1101/2021.04.29.441915
Encoding memory in tube diameter hierarchy of living flow network
Mirna Kramar (author), Karen Alim (author)
2021-03-09
journal article
Proceedings of the National Academy of Sciences
DOI: 10.1073/pnas.2007815118
Tissue-wide integration of mechanical cues promotes effective auxin patterning
João R. D. Ramos (author), Alexis Maizel (author), Karen Alim (author)
2021-02
journal article
The European Physical Journal Plus
DOI: 10.1140/epjp/s13360-021-01204-6
Emergence of behavior in a self-organized living matter network
Philipp Fleig (author), Mirna Kramar (author), Michael Wilczek (author), Karen Alim (author)
2020-09-08
other
DOI: 10.1101/2020.09.06.285080
Living System Adapts Harmonics of Peristaltic Wave for Cost-Efficient Optimization of Pumping Performance
Felix K. Bäuerle (author), Stefan Karpitschka (author), Karen Alim (author)
2020-03-05
journal article
Physical Review Letters
DOI: 10.1103/PhysRevLett.124.098102
Robust Increase in Supply by Vessel Dilation in Globally Coupled Microvasculature
Felix J. Meigel (author), Peter Cha (author), Michael P. Brenner (author), Karen Alim (author)
2019-11-26
journal article
Physical Review Letters
DOI: 10.1103/PhysRevLett.123.228103
Tissue-wide integration of mechanical cues promotes efficient auxin patterning
João R. D. Ramos (author), Alexis Maizel (author), Karen Alim (author)
2019-10-28
other
DOI: 10.1101/820837
The emergent Yo-yo movement of nuclei driven by collective cytoskeletal remodeling in pseudo-synchronous mitotic cycles
2019-06-06
other
[]
URL: http://dx.doi.org/10.1101/662965
DOI: 10.1101/662965

further publications (total of 34).

See ORCID profile of Karen Alim as well.

Top of page