Tom Theile

Understanding the interactions between cells through agent-based simulations
I develop rule based models of cell-cell-tissue-interactions in order to test hypotheses about the underlying mechanisms of intercell communication.

Agent-Potts-Model - An efficient approach to simulate the behavior and shape of cells and cell-populations
A parallel and gridless enhancement of the Cellular Potts Model. Useful for the study of spatio-temporal evolvement of cell-populations.

The source-code is open and available on bitbucket.org. A paper is following soon.

Simulations of bone remodeling principles In agent-based simulations of bone remodeling we can show how osteocytes sense bone damage and initiate bone remodeling events.

Agent-based simulations of the initiation of bone remodeling events for a better understanding of the role of osteocytes
Osteoclasts and Osteoblasts tear down and rebuild the mineralized bone matrix to maintain a healthy and stable bone. Bone remodeling removes microcracks and adopts the bone to changing loads. Pathologic changes of this process can weaken the bone and lead to osteoporosis and spontaneous fractures.
Current empiric methodologies fail to give enough insight into bone remodeling to understand the cellular cooperation to realize bone remodeling. Computer simulations give us the possibility to test concurring hypotheses about the principles of bone remodeling.
A simple spatio-temporal model about the formation and detection of microcracks inside trabecular bone can test different hypotheses about how osteocytes can sense structural damage and mechanical strain inside the bone. We test these Models on real data acquired by micro computed tomography of trabecular bone. We can show how different hypotheses about the cooperation between osteocytes, osteoclasts and osteoblasts result in different efficiencies of the bone remodeling process. The detection of microcracks by osteocytes reduces the number of long microcracks by an order of magnitude at the same remodeling rate. Simple Models with few input parameters like this one can provide clear insights to complex processes. We show quantitatively the importance of a regulatory role of osteocyte - a role that was often postulated but never backed by data before.