ABSTRACT
Original models for functional mapping to study dynamic changes of genetic expression over time or other independent variables were established on the belief that biological processes can be described by mathematical functions (Ma et al., 2002; Wu et al., 2004b). One of the most significant examples for this is the use of Sshaped logistic curves to model growth trajectories. West et al. (2001) indicated from fundamental principles of biophysical processes that logistic forms of growth are biologically crucial for the maintenance of optimal metabolic level and, thereby, the best use of available resources for an organism from birth to adulthood. The advantage of using a parametric function to map dynamic genetic control lies in the estimation and test of biologically meaningful parameters that define curve rates and shapes and the computational prediction of biological processes and events not observed in the study. Such parametric functional mapping provides a quantitative test framework within which a number of biological hypotheses can be asked and tested at the interplay between genetic actions and development.
