We have developed a mathematical model of AT1R-activated signaling kinases and a downstream transcriptional regulatory network controlling the family of activator protein 1 (AP-1) transcription factors. The signaling interactions of the transcriptional model were modeled with either mass-action or Michaelis--Menten kinetics, whereas the phenomenological model of the kinases used exponentials. These models were validated against their respective data domains independently and were integrated into one. The model was implemented as a set of ordinary differential equations solved using the ode15s solver in Matlab (Mathworks, USA).
Model Type: Molecular Network
Cell Type(s): Brainstem neuron
Simulation Environment: MATLAB
Implementer(s): Makadia, Hirenkumar K [hiren.makadia at gmail.com]; Vadigepalli, Rajanikanth [Rajanikanth.Vadigepalli at jefferson.edu]
References:
Miller GM, Ogunnaike BA, Schwaber JS, Vadigepalli R. (2010). Robust dynamic balance of AP-1 transcription factors in a neuronal gene regulatory network. BMC systems biology. 4 [PubMed]
Makadia HK, Schwaber JS, Vadigepalli R. (2015). Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features. PLoS computational biology. 11 [PubMed]