But the cyclical nature of oscillatory systems makes it difficult to identify this functional set of parameters, even when using the most robust optimization routines. This is because the repetitive nature of these systems transforms the bowl into something that looks more like a mountain range, with many hills and valleys. This makes it more complicated and time-consuming to work your way toward accurate parameters.
Since these oscillatory systems present a problem for most optimization algorithms, Williams and NC State Ph.D. student Seyedbehzad Nabavi focused on developing methods that would manipulate the surface characteristics of the objective function itself. This new approach factors in the frequency of the concentrations within the system or how often each concentration is repeated to generate a new objective function that mitigates the impact of system oscillations.
"By generating a new objective function that factors in the frequency of the system oscillations, we are able to eliminate many of the hills and valleys, resulting in a surface with the same optimal point, but that is easier to search," Williams says. "This makes it easier for optimization routines to identify a functional working set of parameters that can then be used to predict the activity of the modeled system."
The paper, "A Novel Cost Function for Parameters Estimation in Oscillatory Biochemical Systems," will be presented at the
|Contact: Matt Shipman|
North Carolina State University