TY - JOUR AU - Kühn, Clemens AU - Wierling, Christoph AU - Kühn, Alexander AU - Klipp, Edda AU - Panopoulou, Georgia AU - Lehrach, Hans AU - Poustka, Albert J. PY - 2009 DA - 2009/08/23 TI - Monte Carlo analysis of an ODE Model of the Sea Urchin Endomesoderm Network JO - BMC Systems Biology SP - 83 VL - 3 IS - 1 AB - Gene Regulatory Networks (GRNs) control the differentiation, specification and function of cells at the genomic level. The levels of interactions within large GRNs are of enormous depth and complexity. Details about many GRNs are emerging, but in most cases it is unknown to what extent they control a given process, i.e. the grade of completeness is uncertain. This uncertainty stems from limited experimental data, which is the main bottleneck for creating detailed dynamical models of cellular processes. Parameter estimation for each node is often infeasible for very large GRNs. We propose a method, based on random parameter estimations through Monte-Carlo simulations to measure completeness grades of GRNs. SN - 1752-0509 UR - https://doi.org/10.1186/1752-0509-3-83 DO - 10.1186/1752-0509-3-83 ID - Kühn2009 ER -