|
pO2
|
10
|
20
|
30
|
40
|
50
|
60
|
70
|
80
|
90
|
100
|
110
|
120
|
|
Y
|
0.18
|
0.4
|
0.65
|
0.8
|
0.87
|
0.92
|
0.94
|
0.95
|
0.95
|
0.96
|
0.96
|
0.97
|
Where pO2 is given in units of mmHg.
Data collected for tetrameric bovine hemoglobin binding to oxygen is given above. Using this data, (a) create the oxygen dissociation curve, perform a linear regression on the experimental data using built-in Matlab function, polyfit, and plot your best-fit model with the data to show that linearity exists.
I think we are supposed to use the Hill equation to capture the sigmoidal shape of the oxygen dissociation curve.
And Henry's equation:
ln(Y/(1-Y)) = n*ln(pO2)+n*ln(P50)
where the model is linear in n and in P50