Some conclusions were made on the characteristics of good Setup 2 parameter sets. This week was spent on figuring out and selecting the pareto sets of the setup 2 parameter set scores.Īs the speed score itself is not very characteristic for the efficiency of the parameter set, a new score takes both time and increased GFP concentration into account. The log-uniform distribution and uniform distributed sets were compared based on speed and GFP scores. This is to run processes continuously and parallel to each other.ĭeveloped second objective score script, aimed at saving the time it takes to reach half of the final GFP concentration. Learned about servers, terminal, screens and how to generate parameters outside the Mac. Included parameterset distributed by log-uniform distribution. Retried with 500,000 parameter sets and learned about lognormal distributions. Generated 100,000 parameters sets, still found too much inconsistency when analyzing the best 10%. Learned how to introduce pulses to the system. The objective used for selecting the best parameter sets was a maximal final GFP concentration that could be formed with those parameters. Here, random parameters were generated using Latin Hypercube sampling. The model gives the concentration of each compound over time, given a set op reaction speeds (parameters).Īs the parameters of most reactions of the system are not known, parameter optimisation can be used. Improved the reaction equations and started writing in Matlab.įirst runs of model. Started on the second model layout (Setup 2), which involves GFPc bound to CpxA and GFPn to CpxR. More system design and learning Matlab (and getting used to my Mac). Aim of the thesis is to compare the systems kinetics, sensitivities and their maximum output. Discussed with receptor and BiFC students on system layout, finally decided on three different ways in which the system could work. Learning Matlab and Modelling basics through a short Maths lecture and multiple exercises.įinished thesis proposal.
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