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| − | .team{width:95%}
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| − | </style>
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| − | <h1 class="title11"></h1>
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| − | <div class="team">
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| − | <h1 class="bigtitle">Making ensemble outputs</h1>
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| − | <p class="title2" style="font-size:25px;">Ensemble ODE’s to pdf’s for observables</p>
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| − | <p style="font-size:17px;">
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| − | From all your data you can output predictions for specific observables for your system. These outputs will be a pdf, more simply a histogram will do. The observables we used were time to reach steady state, time for a given concentration and concentration for a given time. We also produced a plot of concentration vs time for oxidised abts.
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">What can be taken from these things</p>
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| − | From these graphs questions about your system can be answered. In our case does ethanal matter and how does the enzyme act in the second step. This can be done by comparing the results from the lab for these observables with model predictions. For example for the ethanal question we would compare the outputs of uni-bi bi-uni with revmm - bi uni etc. In this case if the histogram for revmm - bi uni was far from the observed values and uni-bi bu uni was close to the observed values you could conclude ethanal does make a difference.
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">HP LINK _ POLICE USAGE</p>
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| − | The cost of the patch can be estimated from the data, setting a maximum time for expression , minimum expression amount and assuming the cost of a patch material is negligible so the total cost is dependant only on the enzyme costs. The cost to produce a patch for all enzyme ratios can be generated. This is then comparable with the current cost of systems like breathalysers (HP - Police interview) to determine if the alcopatch would be relevant to specific industries like the police
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">How code works and Git</p>
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| − | <p style="font-size:17px;">
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| − | Relevant github link. All files discussed here are available for reference.
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| − | <br /><br />
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| − | The codes for these outputs are short and understandable, also there is no guarantee your relevant outputs will be the same. So the files are only included for reference.
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| − | </p>
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| − | <!---------------------------------------------------beer's---------------------------------------------------->
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| − | <h1 style="margin-top:90px;" class="bigtitle">Units and beer’s law</h1>
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| − | <p class="title2" style="font-size:25px;">Why units must be same?</p>
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| − | <p style="font-size:17px;">
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| − | In the lab we could produce concentration vs time graphs, these were simulated using our model.
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| − | We required the units for both to be the same so we could compare.
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">How we did this model?</p>
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| − | For our model our concentrations should be measured in units like mM i.e a measure of the amount of compounds per volume.
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| − | The model units come from the units used in the initial conditions, we used mM by having the concentrations in ug/ml from the lab and dividing by the molecular weight.
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">How we did this experimental?</p>
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| − | <p style="font-size:17px;">
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| − | The experimental team used a plate reader. The units showing concentration over time were optical density values, these can be converted into a concentration using beers law and a calibration experiment.
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">Calibration experiment</p>
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| − | <p style="font-size:17px;">
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| − | The calibration experiment was done with Abts h202 and hrp there was excess H202 so that the equilibrium was such that we could assume all the abts was oxidised. We did this for a range of initial conditions. We now knew the od values at steady state and the concentrations at steady state. And hence we could calibrate.
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| − | <br /><br />
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| − | There were some extra complications because abts decays and the other reagents cause absorbance, these were taken into account initially but the change was negligible so it was ignored, this assumption could be relaxed in the future. This analysis allowed us to convert od values to ug/ml and hence mM.
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">Theory of beer's law</p>
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| − | <p style="font-size:17px;">
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| − | Beer’s law simply states that concentration in a unit like mM is proportional to absorbance measured in od value, a result from fluid mechanics leads to this phenomena specifically with the od scale.
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| − | </p>
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| − | <center>
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| − | <img class="width50" src="https://static.igem.org/mediawiki/2016/f/f8/T--Manchester--modelling_graph_8.png" alt="graph 8" />
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| − | </center>
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| − | <p style="font-size:17px;">The graph is for the described experiment .The dotted line uses the gradient and intercept from fitting. With these you can easily convert between the two.
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| − | </p>
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| − | <p class="title2" style="font-size:25px;">How code works and Git</p>
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| − | <p style="font-size:17px;">
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| − | Relevant github link. All files discussed here are available for reference.
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| − | <br /><br />
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| − | This code is a simple one. Absorbance values in od are read into matlab as well as the concentrations of abts oxidised form the calibration experiment. A straight line fit is then made. Now from this straight lines equation given one variable e.g. absorbance values (od) you can calculate the concentration in (ug/ml.) You could divide by mr to get the answer in mM.
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| − | {{Manchester/CSS/footer}}
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