A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

Studienfachwahl als Spezialfall der Ausbildungsentscheidung und Berufswahl

Recent studies provide empirical evidence on persistence of horizontal inequality of field of study depending on eligible individuals' social origin. In this article we explore the question why there is a correlation between social origin and choice of field of study. Using data from the Saxon survey of high school graduate candidates, we model the decision process of high school students regarding post-secondary education about three month prior to graduation. Our empirical results prove that the effect of social origin on the choice of field of study is the result of an individual decision structured by status maintenance motive, by expected costs for the different types of higher education and training, by individual ability level, by expected success probabilities as well as by the socio-cultural distance to tertiary education. These determinants of the choice of field of study explains the effect of social origin and, therefore for the aggregate, the persistent social inequality of opportunities in the access to field of study