Investigating the two regimes of fibrin clot lysis: an experimental and computational approach
<p> </p> <p><strong>Investigating the two regimes of fibrin clot lysis: an experimental and computational approach</strong></p> <p>Dataset and python files (Python3) to reproduce all figures and simulations presented in the manuscript.</p> <p> </p> <p>**********************<br> * Run_simulations.py *<br> **********************</p> <p>* To run the simulations:<br> python3.8 Run_simulations.py arg1 arg2 arg3 arg4</p> <p> - arg1:<br> Directory with experimental lysis profiles<br> <br> - arg2:<br> Directory to store initial conditions of the lysis (i.e state of the system after clot formation)<br> if the directory does not exist, it is created.<br> <br> - arg3:<br> Directory to store the simulated lysis profiles<br> if the directory does not exist, it is created.</p> <p> - arg4:<br> index of the first set of clotting kinetic parameters (92 sets of parameters)</p> <p> - arg5:<br> index of the last set of clotting kinetic parameters (92 sets of parameters)</p> <p>* Example: python3.8 Run_simulations.py Raw_Data/ Init/ Results/ 0 92</p> <p><br> * Requires:<br> - module_fibrin_polymerization_Diamond_kinetics.py<br> - module_kinetics.py<br> - solid_Diamond_Anand_dict.py (dictionnary with parameters of the simulations)<br> - output_parameters_polymerization_T1000.txt (sets of clotting kinetic parameters)<br> - Mean_LAT_LYS_shell.txt (mean fraction of shells during slow and fast lysis for each experiment. Used to compute the distribution of shells for the surrogate model)</p> <p><br> ****************************************<br> * make_analysis_figures_simulations.py *<br> ****************************************</p> <p>* To reproduce the figures associated to simulation results:<br> python3.8 make_analysis_figures_simulations.py arg1 arg2 arg3 arg4</p> <p> - arg1:<br> Directory with experimental lysis profiles</p> <p> - arg2:<br> Directory with the simulated lysis profiles</p> <p> - arg3:<br> Directory with initial conditions</p> <p> - arg4:<br> Directory with the results of the sensitivity analysis</p> <p>* Example: python3.8 make_analysis_figures_simulations.py Raw_Data/ Results/ Init/ Sensitivity_Analysis/</p> <p>* PDF Figures are created in the current directory</p> <p>* Requires:<br> - module_analyze_simulations.py<br> - module_analyze_data.py<br> - output_parameters_polymerization_T1000.txt<br> - manip_summary.txt (clot formation time, slow lysis time, fast lysis time for each experiment)<br> - Experiments_sorted.txt (experimental conditions, sorted by increasing order of concentrations)</p> <p><br> ****************************************<br> * make_analysis_figures_experiments.py *<br> ****************************************</p> <p>* To reproduce the figures associated to experimental results:<br> python3.8 make_analysis_figures_experiments.py arg1</p> <p> - arg1:<br> Directory with experimental lysis profiles</p> <p>* Example: python3.8 make_analysis_figures_experiments.py Raw_Data/</p> <p>* PDF Figures are created in the current directory</p> <p>* Requires:<br> - module_analyze_data.py<br> - Experiments.txt (contains experimental conditions)</p> <p> </p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4
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