![]() IF you have repeated measures, NO! Your model currently assumes that the errors are independent, which is not true when a given subject is measured across time.The second one is even easier: you can as R to give you ALL pairwise comparisons and look at the differences within Time points. Therefore, the interaction between these two variables allows you to ask nice things! You could ask (e.g.) two things: 1) Is there an effect of Time (Linear, Quadratic, etc.) for each Treatment? and 2) Is there difference across Treatments within each Time point? These two questions can be obtained by writing contrasts. ![]() This is not a standard way to view ANOVA results, but it can be informative. What would be an appropriate way to find the significance of the timepoints for each comparison of treatments? A: THe kind of design you have is very interesting: You have a discrete variable (treatment) and a quantitative variable (time). Prism fits two models to the data - one where all the groups are sampled from populations with identical means, and one with separate means - and tells you the likelihood that each is correct.Is there a compelling reason to use a repeated measures approach with this data? A: If a given individual is measured at "2 Months" and then measured again at "4 Months", yes, you can potentially (maybe you should) use repeated measures for this data.The only requirement is to use protein and ligand concentrations in the range of Kd so that you can actually see binding variation when total protein concentration varies (in your experiment it is expected a nanomolar Kd).Īnswering your questions (things may change depending on your answer above): The approximation X=total protein is made when total protein is much greater than total ligand. ![]() So in the equation if Y is bound DNA then Bmax is total DNA and X has to be free protein (total protein minus bound protein). In your case of EMSA, you easily spot and quantify bound and free forms of DNA on gel and knowing protein has a single binding site for DNA, it means that bound DNA is also bound protein. ![]() For the latter, there is no absolute need to have a large excess of one of the components as long as you can identify bound and free forms of the ligand or of the protein. I think you are doing a mix between enzyme activity determination where it is important to work in large excess of substrate (in order to observe initial velocities for Km, Vm determination) and condition for Kd determination for protein ligand interaction. ![]()
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