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The use of genetic tools, imaging technologies and ex vivo culture systems has provided significant insights into the role of tissue inducer cells and associated signaling pathways in the formation and function of lymphoid organs. Despite advances in experimental technologies, the molecular and cellular process orchestrating the formation of a complex three-dimensional tissue is difficult to dissect using current approaches. Therefore, a robust set of simulation tools have been developed to model the processes involved in lymphoid tissue development. Specifically, the role of different tissue inducer cell populations in the dynamic formation of Peyer's patches has been examined. Utilizing approaches from systems engineering, an unbiased model of lymphoid tissue inducer cell function has been developed that permits the development of emerging behaviors that are statistically not different from that observed in vivo. These results provide the confidence to utilize statistical methods to explore how the simulator predicts cellular behavior and outcomes under different physiological conditions. Such methods, known as sensitivity analysis techniques, can provide insight into when a component part of the system (such as a particular cell type, adhesion molecule, or chemokine) begins to have an influence on observed behavior, and quantifies the effect a component part has on the end result: the formation of lymphoid tissue. Through use of such a principled approach in the design, calibration, and analysis of a computer simulation, a robust in silico tool can be developed which can both further the understanding of a biological system being explored, and act as a tool for the generation of hypotheses which can be tested utilizing experimental approaches.

Original publication




Journal article


Front Immunol

Publication Date





Peyer’s patches, agent-based modeling, computational modeling, development, lymphoid tissue inducing cells, lymphoid tissue organizer cells, sensitivity analysis