Metabolism represents a complex system characterised by a high variability in metabolites' structure, concentration and regulation ratio. Such variability is observed at different metabolic scales going from metabolites to metabolic profiles via chemical reactions and metabolic pathways, as well as under static or dynamic aspects. Variations in these components are due to apparition-disappearance, level increase-decrease and/or relative changes in weights or contributions leading to different structural, functional and evolutive states of the metabolic system. This book presents a variety of different computational approaches of the variability in metabolic systems.

This is a book which presents several step-by-step complementary and chained statistical tools. These tools are applied to analyse structures and variability of natural systems helping to gradually understand and control their complexity. The book is organised into a series of chapters which are extensively illustrated by intuitive figures and simple numerical examples. Statistics represent a large field of applied mathematics aiming to extract and analyse information from sampled data issued from complex systems or populations. Extraction of reliable information on systems requires "a priori" of the application of strategic rules by which intrinsic variability and extrinsic limits are considered. Such strategic rules are given by sampling designs and experimental designs which are applied for open and close systems, respectively. Sampling designs presented in this book include simple random, systematic and stratified designs which are applied to estimate and control variability in open systems having different organisations or distributions. Moreover, sampling designs are appropriate tools for later biodiversity and spatiotemporal analysis of natural systems. Experimental designs include factorial, response surface and mixture designs which are specifically applied to control systems defined by different geometrical structures. Such geometrical structures have different dimensions defined by strategic values of experimental factors which could have potential effects on the studied system.