Figure 6

Prior information on E _fr improves estimate. Approximate posterior distributions for E _fr (upper panels) and K _d (lower panels) obtained from using the MCMC algorithm to analyze the same datasets in the absence (red) or presence (blue) of prior knowledge about E _fr show that prior knowledge helps to improve accuracy and reduce uncertainty of the estimate. True values are indicated by vertical dashed lines and the inset shows the prior distributions used (red is a uniform distribution and blue is a normal distribution centred at 0.45 with a variance of 0.15). The plots on the left show results from analyzing data where 10 measurements were made in each channel for each of 3 cells with [A₀] = [D₀] = [.2, 1, 5]·10^-6M. The plots on the right show results from data from the same cells, but with just 3 measurements/channel. 20,000 steps were recorded for each biased biased random walk, with 5% added noise. For other parameter values, see Methods.