title: In-silico models of stem cell and developmental systems.
abstract: Understanding how developmental systems evolve over time is a key question in stem cell and developmental biology research. However, due to hurdles of existing experimental techniques, our understanding of these systems as a whole remains partial and coarse. In recent years, we have been constructing in-silico models that synthesize experimental knowledge using software engineering tools. Our approach integrates known isolated mechanisms with simplified assumptions where the knowledge is limited. This has proven to be a powerful, yet underutilized, tool to analyze the developmental process. The models provide a means to study development in-silico by altering the model's specifications, and thereby predict unforeseen phenomena to guide future experimental trials. To date, three organs from diverse evolutionary organisms have been modeled: the mouse pancreas, the C. elegans gonad, and partial rodent brain development. Analysis and execution of the models recapitulated the development of the organs, anticipated known experimental results and gave rise to novel testable predictions. Some of these results had already been validated experimentally. In this paper, I review our efforts in realistic in-silico modeling of stem cell research and developmental biology and discuss achievements and challenges. I envision that in the future, in-silico models as presented in this paper would become a common and useful technique for research in developmental biology and related research fields, particularly regenerative medicine, tissue engineering and cancer therapeutics.
authors.affiliation: Computational Systems Biology, Max-Planck-Institut für Informatik, Saarbrücken 66123, Germany. yaki.setty@gmail.com.
authors.forename: Yaki
authors.initials: Y
authors.lastname: Setty
mesh_terms: D000818:Animals; D002454:Cell Differentiation; D003198:Computer Simulation; D008954:Models, Biological; D013234:Stem Cells / Q000166:cytology*