Supporting material. The file contains detailed stability analysis of Models 1-4; theoretical analysis showing how auto-inhibition increases τ m ; demonstration how τ m can be increased by auto-inhibition for the p53 model; details of robustness analysis of the optimal solution for the p53 model; modelling the switch from oscillatory to adaptive response of the p53 system; calculating the duration of “On” and “Off” states of p53 pulses; figure demonstrating the dependence between parameter values of Models 1-4 and τ m ; figure with results of Monte-Carlo analysis of Models 1-4 applied to the alternative parameter set; table with the best-fit parameters for the p53 model. (PDF 1044 kb
This study proposes a two-dimensional (2D) oscillator model of p53 network, which is derived via red...
Figure S1. Few representative replicas from the sample set of the switching function gives better un...
Recent experimental observations reveal that local cellular contraction pulses emerge via a combinat...
Parameter values as indicated in the figure/caption. (A) Block diagram of the bistable, delayed nega...
The p53 tumour suppressor protein is a transcription factor that activates genes that result in cell...
<p>Time response at a steady state fixed at . The red and blue plots denote the cases with and witho...
Deterministic and stochastic Boolean network models are built for the dynamics of negative feedback ...
Supplemental Information. Additional information including supporting figures, the generalized conce...
Parameter values as given in Table 1 or as indicated in the figure/caption. (A) Mass-action model of...
In response to cellular stress, such as DNA damage, the tumor suppressor p53 is activated to regulat...
Differential equation models for biological oscillators are often not robust with respect to paramet...
The tumor suppressor p53 has become one of most investigated genes. Once activated by stress, p53 le...
Background: One of the distinctive features of biological oscillators such as circadian clocks and c...
The tumor suppressor p53 has become one of most investigated genes. Once activated by stress, p53 le...
From a system theory perspective, p53 network dynamics is interesting since it can exhibit three dyn...
This study proposes a two-dimensional (2D) oscillator model of p53 network, which is derived via red...
Figure S1. Few representative replicas from the sample set of the switching function gives better un...
Recent experimental observations reveal that local cellular contraction pulses emerge via a combinat...
Parameter values as indicated in the figure/caption. (A) Block diagram of the bistable, delayed nega...
The p53 tumour suppressor protein is a transcription factor that activates genes that result in cell...
<p>Time response at a steady state fixed at . The red and blue plots denote the cases with and witho...
Deterministic and stochastic Boolean network models are built for the dynamics of negative feedback ...
Supplemental Information. Additional information including supporting figures, the generalized conce...
Parameter values as given in Table 1 or as indicated in the figure/caption. (A) Mass-action model of...
In response to cellular stress, such as DNA damage, the tumor suppressor p53 is activated to regulat...
Differential equation models for biological oscillators are often not robust with respect to paramet...
The tumor suppressor p53 has become one of most investigated genes. Once activated by stress, p53 le...
Background: One of the distinctive features of biological oscillators such as circadian clocks and c...
The tumor suppressor p53 has become one of most investigated genes. Once activated by stress, p53 le...
From a system theory perspective, p53 network dynamics is interesting since it can exhibit three dyn...
This study proposes a two-dimensional (2D) oscillator model of p53 network, which is derived via red...
Figure S1. Few representative replicas from the sample set of the switching function gives better un...
Recent experimental observations reveal that local cellular contraction pulses emerge via a combinat...