Microcomputer-based nonlinear regression analysis of ligand-binding data: application of Akaike's information criterion.
Akaike's information criterion (AIC) (Akaike, H., IEEE Trans. Automat. Contr. AC-19, 716-723 (1974)) was applied to estimate statistically the number of classes of binding sites from ligand-binding data. Several sets of data were analyzed by both the AIC method and the F-test method. Good agreement was obtained between results from both methods. The present results suggest that the AIC method can be a good alternative to the F-test to estimate the number of classes of sites.
D000818:Animals; D001665:Binding Sites; D002417:Cattle; D003201:Computers; D004174:Diprenorphine / Q000378:metabolism; D004723:Endorphins / Q000378:metabolism; D008838:Microcomputers; D011869:Radioligand Assay; D051381:Rats; D012044:Regression Analysis; D001615:beta-Endorphin
D004723:Endorphins; D004174:Diprenorphine; D001615:beta-Endorphin