Estimating confidence intervals in predicted responses for oscillatory biological models.

ABSTRACT:

Background

The dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network's structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model's parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is

SUBMITTER: St John PC 

PROVIDER: S-EPMC3733791 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature