Supporting materials for Akhmetzhanov AR, Kim JW, Sullivan R, Beckman RA, Tamayo P, Yeang CH 2019 "Modelling bistable tumour population dynamics to design effective treatment strategies." J Theor Biol doi:10.1016/j.jtbi.2019.05.005
The code scripts can be viewed in sequential order.
Main part of the analysis with generating most of the figures
- A. Main analysis and resulting figures [Python].ipynb
- B1. Solution of the control problem including the universal line and Sensitivity analysis [Python].ipynb
Whereas, three variations for different values of the cost of resistance:
- B2. (lower cost of resistance) Solution of the control problem including the universal line and Sensitivity analysis [Python].ipynb
- B3. (higher cost of resistance) Solution of the control problem including the universal line and Sensitivity analysis [Python].ipynb
- B4. (much higher cost of resistance) Solution of the control problem including the universal line and Sensitivity analysis [Python].ipynb*
Sensitivity analysis:
- C1. Sensitivity analysis [R].ipynb
- C2. Sensitivity analisys - second part - computations for Fig S7 [Python].ipynb
Construction of the field of optimal trajectories:
- D. Field of optimal trajectories [Python].ipynb
- D-2. Field of optimal trajectories for different time horizons [Python].ipynb
Lastly, generation of last two figures (possibly the naming is incorrect):
Written by Andrei R. Akhmetzhanov 2019