2. Calculate the amount of avidin i.e. A(avidin) in each well.
Formula you can use:
C(avidin) X Volume
Where C(avidin) is the concentration of avidin in µg/mL, volume is the total volume in the well in mL and MW is the molecular weight of avidin – you will have to find the molecular weight of avidin from literature!
3. Subtract the averaged no-avidin control baseline data from all other data. Average all replicates, remembering to exclude obvious outliers or anomalous data (explain which and why excluded). Draw a graph with amount of avidin (pmoles) on the X-axis, which is best plotted on a Log scale, and absorbance on Y-axis. Please include error bars representing standard error in the mean (SEM). Find out the limit of detection of avidin (above baseline) from the graph. You may observe a linear section above baseline and perhaps a plateau region. What could explain a plateau towards an apparent maximum absorbance?
4. Calculate the concentration of unlabeled biotin added to each well) – remember that you have serially diluted the stock biotin solution; each well will have a different dilution factor!
5. Calculate the concentration of Biotin (μM) in each well, taking into account the dilution from the stock.
6. Again, average and subtract baseline absorbance data. It is then worth normalizing your absorbance measures to the maximum absorbance (with no biotin added) by dividing all other data by averaged no-biotin data. Now 1.0 is maximum or can multiply by 100 if you wish to express as a %. Average your normalized replicate data and determine the standard deviation (SD) or preferably standard error in the mean (SEM) for inclusion as error bars.
7. Pasting transposed data into columns helps with grap
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