Scripts to perform dynamic optimization of a model of invasive aspergillosis

<p>Matlab scripts to perform optimization and analyses of a dynamic optimization model of invasive aspergillosis:<br> &quot;Dynamic optimization reveals alveolar epithelial cells as key mediators of host defense in invasive aspergillosis&quot;<br> Jan Ewald, Flora Rivieccio, Luk&aacute;&scaron; Radosa, Stefan Schuster, Axel A. Brakhage, Christoph Kaleta<br> https://doi.org/10.1101/2021.05.12.443764</p> <p>File structure:</p> <p>--- Core optimization files ---<br> -- simulation.cpp --<br> Description of ODE model in &#39;C&#39;, used by solver to calculate the time course given the parameters, initial states and control variables</p> <p>-- simulation.mexa64 --<br> Compiled mex-File from simulation.cpp used as interface by MATLAB to &#39;C&#39; files.</p> <p>-- optFun.m --<br> Definition of the objective function. Uses a control vector &#39;u&#39; to calculate the, objective function value F, the time course of state variables &#39;x&#39; and gradients used by the solver to determine the optimal control of &#39;u&#39;.</p> <p>-- single_opt.m --<br> Function which performs an optimization run for a given parameter set and a randomized initial solution u0. Optimization can be conducted by SNOPT or in conjunction with IPOPT. Both solver are not provided here (proprietary).</p> <p><br> --- Additional files ---<br> -- solve_with_ipopt.m --<br> Configuration file and interface to call the solver IPOPT.</p> <p>-- lognorm_mu.m --<br> Function to provide log-normal distributed samples given the standard deviation, reference value (mode of distribution) and number of samples which should be calculated.</p> <p>-- mice_param_alv.m --<br> Reference parameter set of the model for mice as host organism and cell numbers normalized per alveolus.</p> <p>-- parameter_model.m --<br> Definition of parameter container to handle interface to optFun-call by solvers which do not allow parameter in function call.</p> <p>--- Optimization Runs ---<br> -- rand_params.m --<br> Performs optimization runs for multiple randomized parameter sets and several scenarios to determine parameter sensitivity.</p> <p>-- doseresponse.m --<br> Performs optimization runs for a sequnce of initial conidial dosages to determine the dose response of the system.</p> <p>--- Scripts for post-analysis ---<br> -- rand_analysis.m --<br> Loads the data created by the optimization runs (rand_params.m) and performs parameter sensitivity analysis as well as produces plots for analysis related to parameter influence.</p> <p>-- doseanalysis.m --<br> Loads the data created by the optimization runs (doseresponse.m ) and produces dose response curves as well as additional plots and analyses.</p> <p>--- Optimization output files ---<br> -- rand_param_out/ --<br> Folder contains optimization results as MATLAB session-file for randomized parameters used for parameter sensitivity analysis.</p> <p>-- dose_out/ --<br> Folder contains optimization results as MATLAB session-file for dose response curve calculation.</p>