title: Mathematical Models of Pluripotent Stem Cells: At the Dawn of Predictive Regenerative Medicine.
abstract: Regenerative medicine, ranging from stem cell therapy to organ regeneration, is promising to revolutionize treatments of diseases and aging. These approaches require a perfect understanding of cell reprogramming and differentiation. Predictive modeling of cellular systems has the potential to provide insights about the dynamics of cellular processes, and guide their control. Moreover in many cases, it provides alternative to experimental tests, difficult to perform for practical or ethical reasons. The variety and accuracy of biological processes represented in mathematical models grew in-line with the discovery of underlying molecular mechanisms. High-throughput data generation led to the development of models based on data analysis, as an alternative to more established modeling based on prior mechanistic knowledge. In this chapter, we give an overview of existing mathematical models of pluripotency and cell fate, to illustrate the variety of methods and questions. We conclude that current approaches are yet to overcome a number of limitations: Most of the computational models have so far focused solely on understanding the regulation of pluripotency, and the differentiation of selected cell lineages. In addition, models generally interrogate only a few biological processes. However, a better understanding of the reprogramming process leading to ESCs and iPSCs is required to improve stem-cell therapies. One also needs to understand the links between signaling, metabolism, regulation of gene expression, and the epigenetics machinery.
authors.affiliation: Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK. pnarpir@gmail.com.
authors.forename: Pınar
authors.initials: P
authors.lastname: Pir
authors.affiliation: Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK. n.lenovere@gmail.com.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Le Novère
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D039904:Pluripotent Stem Cells; D044968:Regenerative Medicine / Q000379:methods; D015203:Reproducibility of Results; D033581:Stem Cell Transplantation / Q000379:methods
keywords: Mathematical modeling; Pluripotency; Predictive models; Regenerative medicine; Stem cells; Systems biology