Results:
- Plot each boxplot with raw data
- Put initial concentration
- Plot all parameter clusters
- Calculate raw data
	- Calculate variance of each parameter
	- Select the parameter having the smallest variance
	- Also calculate the coefficient of variation
	- Parameter with very large variance -- parameter is robust and not important for model*
	- PLOT for each parameter find the CV
	- on the y-axis: CV, on the x-axis: parameter
- Resolve difference between cytochrome c reduced and cytochrome c total
- Range:
	- Take the values from the best 10 % solutions
- Have confidence interval:
	- In parameter table have a range for best 10% solutions
	- Average +- std. error
	- Keep value for best value
- In all the boxplots, add the cytochrome c total
- Verify boxplot range
	- Try x - max instead of just x - min
- Also calculate z-scores and make boxplots that way
- Can also look covariance for each set of parameters within in complex unit
Paper:
- Add in conclusion
	- Add prediction
	- Add slice plots for predictions
	- Cite Alzheimer's paper
- Remove interpretation from results
Add meeting from Sept 6 2016
Add meeting from Sept 6 2016