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Python scripts used to simulate the model and calculate Pareto sets from paper "How to design an optimal sensor network for the unfolded protein response" [Mol Biol Cell 29 (2018), 3052-3062]. All codes were run using Python, version 2.7.
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bifurcation_analysis
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README.md
delayed_nf_upr_piecewise_and_switch.py
delayed_nf_upr_piecewise_cf_switch.py
delayed_nf_upr_piecewise_u_switch.py
gridsearch_compare_switches.py
gridsearch_plot_pareto_integrals.py
gridsearch_run_batch.py
plat_ANDswitch.py
plat_Cfswitch.py
plat_Uswitch.py
plot_multiple_pareto_fronts_Umin_Cfmax.py
plot_multiple_pareto_fronts_Umin_Cfmax_wUmax.py
plot_multiple_phase_planes_Umin_Cfmax.py
plot_multiple_phase_planes_Umin_Cfmax_AND.py
plot_piecewise_switch.py

README.md

Pareto-UPR-Feedback-Control

Python scripts used to simulate the model and calculate Pareto sets from paper "How to design an optimal sensor network for the unfolded protein response" [Mol Biol Cell 29 (2018), 3052-3062]. All codes were run using Python, version 2.7. This code was originally created by Wylie Stroberg. For more information, we recommend to read the paper on: https://www.molbiolcell.org/doi/10.1091/mbc.E18-01-0060 If you use our code, please cite our manuscript.

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