Modelling of indirect cell-cell interaction networks mediated by IFNγ/IL-4 cytokine involved in atopic dermatitis.

Atopic dermatitis (AD) is an immune-driven inflammatory skin disease that is known to have a significantly high life-time prevalence in the human population. T-helper (Th) immune cells play a key role in the pathogenesis of AD which is marked by defects in the skin barrier function along with a significant increase in the population of either Th1 or Th2 sub-types of Th cells. The progression of AD from the acute to chronic phase is still poorly understood, and here we explore the mechanism of this transition through the study of a mathematical model for indirect cell-cell interactions among Th and skin cells via the secreted cytokines IFNγ and IL-4, both known to have therapeutic potential.

A stochastic model of homeostasis: The roles of noise and nuclear positioning in deciding cell fate.

We study a population-based cellular model that starts from a single stem cell that divides stochastically to give rise to either daughter stem cells or differentiated daughter cells. There are three main components in the model: nucleus position, the underlying gene-regulatory network, and stochastic segregation of transcription factors in the daughter cells. The proportion of self-renewal and differentiated cell lines as a function of the nucleus position which in turn decides the plane of cleavage is studied.

Transition and identification of pathological states in p53 dynamics for therapeutic intervention.

We study a minimal model of the stress-driven p53 regulatory network that includes competition between active and mutant forms of the tumor-suppressor gene p53. Depending on the nature and level of the external stress signal, four distinct dynamical states of p53 are observed. These states can be distinguished by different dynamical properties which associate to active, apoptotic, pre-malignant and cancer states.