Quantitative stem cell biology: computational studies in the hematopoietic system.
OBJECTIVE
This review is intended to provide an overview of recently published computational methods, including bioinformatic algorithms, mathematical models and simulation studies, applied to stem cell biology, with particular reference to the hematopoietic system.


RESULTS
The analysis of molecular data is making an increased contribution to identify dynamic system responses. Specifically, there are promising computational approaches to characterizing the functional interrelation of network components regulating the process of differentiation and lineage specification of hematopoietic stem cells. Furthermore, evidence is accumulating that stem cell organization should be regarded as a flexible, self-organizing process rather than as a predetermined sequence of events. A number of mathematical models relevant to the hematopoietic (stem cell) system are applied successfully to clinical situations, demonstrating the predictive power of theoretical methods.


CONCLUSIONS
Based on the advances in measurement technology, an increasing amount of cellular and molecular data is being generated within the field of stem cell biology. The complexity of the underlying systems, however, most often limits a direct interpretation of the data and makes computational methods indispensable. Mathematical models and simulation techniques are contributing considerably to the discovery of general regulatory principles of stem cell organization and are providing clinically relevant predictions.
Roeder
Ingo
I
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany. ingo.roeder@imise.uni-leipzig.de
D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods / Q000639:trends; D003198:Computer Simulation / Q000639:trends; D006410:Hematopoiesis / Q000502:physiology* / Q000528:radiation effects*; D006801:Humans; D008954:Models, Biological