Use of Randomized Sampling for Analysis of Metabolic Networks

摘要: Genome-scale metabolic network reconstructions in microorganisms have been formulated and studied for about 8 years. The constraint-based approach has shown great promise analyzing the systemic properties of these reconstructions. Notably, models used successfully to predict phenotypic effects knock-outs engineering. inherent uncertainty both parameters variables large-scale is significant well suited study by Monte Carlo sampling solution space. These techniques applied extensively reaction rate (flux) space networks, with more recent work focusing on dynamic/kinetic properties. as an analysis tool many advantages, including ability missing data, apply post-processing techniques, quantify optimize experiments reduce uncertainty. We present overview this emerging area research systems biology.