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Bacterial cell growth fit modeling with stacked data

I'm super new to JMP and was wondering if there's a way to fit a bacterial growth curve (sigmoidal) in order to extract the growth rate. The way I usually do this is by plotting the curve in excel, picking the points the correspond to exponential growth (the middle of the curve), plotting those on a log scale y axis and adding an exponential fit trendline. The exponential coefficient in the trendline equation corresponds to the growth rate, which is what I need. I then have to repeat that process for each growth curve replicate that I have and then I finally manually calculate the standard deviation between replicates.


I've been playing around with JMP and looked into the cell growth 4p nonlinear fit model and the cell division aspect of the equation seems to roughly correlate with my manually calcuated growth rates, but I'm honestly not sure if they're the same thing or not. Also, I can't find a way to fit three replicate curves that have been stacked; whenever I plot them and pick "mean" as the summary statistic I then try to model the averaged curves and the new window that pops up has all three curves as separate. Any help would be appreciated! TIA!


Re: Bacterial cell growth fit modeling with stacked data

Hi @PriorChipmunk23 ,


Here is one way that might help you:


In Fit Curve you can find the closest model (as you already did) and save out the parametric prediction formula:



You can then go to the Nonlinear Platform, using this formula as the predictor, and your output variable as Y. Hit “Go” to start the fitting process, and then you can save prediction formula, Standard Error, formulae for confidence limits or just the limit values:




If you want to do this by batch, simply put the column with the batch-ID in the “By”-Window in the launch dialogue. It will then launch as many fitting dialogues as you have levels in your Batch-ID column.


Hope this helps!