Abstract
The problem of choosing the number and spacing of experimental measurements in order to distinguish between several important biochemical models is investigated. Functionals S n (ϑ_), Q (ϑ_) and R ( n ) are introduced as optimal design criteria for model discrimination with multiple ligand binding sites, consecutive compartmental transport and denaturation of independent isoenzymes. Software to calculate these functionals and record their behavior as functions of the true parameter vector ϑ_ and the number of design points n is described. Optimisation over a subset of possible designs suggests that geometrically increasing spacing is to be preferred. This conclusion and conclusions about the number of measurements required are also reinforced by Monte Carlo simulation using the F -test for model discrimination.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
