Growth curves can be divided into phases (lag, exponential, stationary and death) and each has its pitfalls.
Showing posts with label matlab. Show all posts
Showing posts with label matlab. Show all posts
Tuesday, 23 August 2016
Methodological sabotage of growth rates
Following the interest in a previous post about analysing growth curves in Matlab I would like to discuss issues in growth curves that can arise from the methodological/biological side of things. Fitting the data is perfect if the data is perfect, if not, looking at what is wrong by eye is warranted for future corrections.
Growth curves can be divided into phases (lag, exponential, stationary and death) and each has its pitfalls.
Growth curves can be divided into phases (lag, exponential, stationary and death) and each has its pitfalls.
Wednesday, 23 March 2016
Growth curves
> All scripts mentioned can be found on https://github.com/matteoferla/growth_curves
> Another post discusses what methodological errors can ruins growth rates
Bacterial growth curves never look like they are in the textbooks as sick bacteria are the worst patients.
Fitness is possibly one of the top three buzzwords in evolutionary biology. It encompasses the more subtle effects that lie between death or growth. However, measuring fitness via growth rates is easier say than done. Especially since auxotrophs and bradytrophs have quirkier behaviours than prototrophs.
> Another post discusses what methodological errors can ruins growth rates
Bacterial growth curves never look like they are in the textbooks as sick bacteria are the worst patients.
Fitness is possibly one of the top three buzzwords in evolutionary biology. It encompasses the more subtle effects that lie between death or growth. However, measuring fitness via growth rates is easier say than done. Especially since auxotrophs and bradytrophs have quirkier behaviours than prototrophs.
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