Mathematical Modeling of Stem-Cell-Driven Processes
Adult stem cells are unspecialized cells with the ability to give rise to multiple types of functional cells. Rare quantities of adult stem cells exist in many tissues. Their population persists over the whole life and they are responsible for tissue maintenance, repair and regeneration. For this reason stem cells play an important role in regenerative medicine.
Similar as healthy tissues many cancers are maintained by stem cells. The so-called cancer stem cells are maligant cells that give rise to the cancer cell bulk. Cancer stem cells are resistant to standard treatments and trigger relapse.
Mechanistic mathematical models are a description of biological processes in mathematical terms. They allow to rigorously study complex systems using mathematical tools and computer simulations. Mathematical models help to compare competing hypotheses and to quantify processes that cannot be measured directly. Thus they provide insights that are complementary to experimental knowledge.
Especially in a clinical setting experimental possibilities are limited. Mathematical models can help to quantify relevant disease characteristics based on data from individual patients. This is an important contribution to personalized medicine. Classification of individual disease dynamics, personalized risk scoring and adaptation of treatment schedules to the specific needs of a patient are important aims of mathematical modeling in systems medicine/computational medicine.
The links below provide an overview of specific research topics and results.
Blood cell formation and stem cell transplantation
Blood cell formation (hematopoiesis) is maintained by hematopoietic stem cells (HSC) that reside in the bone marrow and give rise to all types of mature blood cells. Mathematical models help to understand how blood cell formation is regulated and how this can be used to optimize clinical interventions such as bone marrow transplantation.
Cancers of the blood forming system
Cancers of the blood forming system are a very heterogeneous group of diseases. An important example is acute myeloid leukemia. It is driven by leukemic stem cells that resist treatment and trigger relapse. Mathematical models can help to characterize leukemic stem cell properties and to predict the clinical course of the disease.
Stem cell aging
The regenerative capacity and the functionality of tissues decline with age. These processes are related to changes of stem cell properties. Especially in the context of regenerative medicine or tissue transplantations it is relevant to understand and counteract age-related stem cell impairments. Mathematical models can help to understand and quantify how stem cell properties change with age.
Adult Neurogenesis
Learning and cognition require lifelong formation of neurons. Formation of neurons in the adult brain is driven by a small population of neural stem cells. Mathematical models help to quantify neural stem cell properties and their change during aging.
Plant stem cell dynamics
Plants maintain pools of active stem cells to continuously generate new organs such as leaves and flowers. The plant stem cells are located in specialized tissues, so-called meristems. Mathematical models contribute to the mechanistic understanding of meristem regulations and mutant phenotypes.
Others
- Model reduction and quasi-steady state approximation
- Multi-scale modeling of mammalian follicular development