Network functionality

From the previous discussion, it is clear that ART networks are more applicable for pattern recognition than for quantitative applications. In Fig. 44.27 it is shown how ART networks functions with different values for p. It has been applied to... 

The parameters of neutron scattering theory of polymer networks are A, the macroscopic stretching of the sample, or linear degree of swelling, f, the network functionality, K. which accounts for restricted junction fluctuations and a, a measure of the degree to which chain extension parallels the macroscopic sample deformation. The functionality is known from knowledge of the chemistry of network formation, and A is measured. Both K and a must be extracted from experiments. 

Figure 2. Dependence of the structure factors, A, As, and A,. The ratio At/At on network functionality for Mn is 21,600 networks (1).

Key 9, A, , commercial a,a-divinyl PDMS networks O, A, . narrow molecular weight distribution a,a-divinyl PDMS networks. Functionality , 10.58 ,... 

Delcroix, M., Sajid, M., Caffrey, C.R., Lim, K.-C., Dvorak, J., Hsieh, I., Bahgat, M., Dissous, C., and McKerrow, J.H. (2006) A multienzyme network functions in intestinal protein digestion by a platy-helminth parasite./. Biol. Chem. 281, 39316-39329. 

Transcriptional regulator networks function in invertebrate development 445... 

Considering a trade-off between knowledge that is required prior to the analysis and predictive power, stoichiometric network analysis must be regarded as the most successful computational approach to large-scale metabolic networks to date. It is computationally feasible even for large-scale networks, and it is nonetheless far more predictive that a simple graph-based analysis. Stoichiometric analysis has resulted in a vast number of applications [35,67,70 74], including quantitative predictions of metabolic network function [50, 64]. The two most well-known variants of stoichiometric analysis, namely, flux balance analysis and elementary flux modes, constitute the topic of Section V. 

The stoichiometric matrix N is one of the most important predictors of network function [50,61,63,64,68] and encodes the connectivity and interactions between the metabolites. The stoichiometric matrix plays a fundamental role in the genome-scale analysis of metabolic networks, briefly described in Section V. Here we summarize some formal properties of N only. 

Incorporation into the network of specific substructures determining the network functions. 

The network function is determined by the network structure (i.e., the particular mode by which the individual neurons are connected to one another), the connection strengths (synaptic weights) (i.e., the quantitative rules defining the information transfer), and the processing performed at the individual neuron. 

In this study we showed that the biochemical networks function according to the mode of connection between the basic systems (e.g., network A, B, or C), and also according to the processing performed at each neuron (i.e., reaction mechanism or kinetic constants). For the biochemical systems, the strengths of connection between basic elements (i.e., synaptic weights) is represented by the concentration of the component that is shared between the neurons. 

Le Moal M, Simon H (1991) Mesocorticolimbic dopaminergic network functional and regulatory roles. Physiol Rev 77 155-234. 

The ultimate example studied in this chapter is the mitochondrial respiratory system and oxidative ATP synthesis. This system, in which biochemical network function is tightly coupled with membrane transport, is essential to the function of nearly all eukaryotic cell types. As an example of a critically important system and an analysis that makes use of a wide range of concepts from electrophysiology to detailed network thermodynamics, this model represents a milestone in our study of living biochemical systems. To continue to build our ability to realistically simulate living systems, the following chapter covers the treatment of spatially distributed systems, such as advective transport of substances in the microcirculation and exchange of substances between the blood and tissue. 

Metabolic fluxes are responsible for maintaining the homeostatic state of the cell. This condition may be translated into the assumption that the metabolic network functions in or near a non-equilibrium steady state (NESS). That is, all of the concentrations are treated as constant in time. Under this assumption, the biochemical fluxes are balanced to maintain constant concentrations of all internal metabolic species. If the stoichiometry of a system made up of M species and N fluxes is known, then the stoichiometric numbers can be systematically tabulated in a... 

Figure 5.17 (a) Illustration of types of chain association in telechelic polymers. (b) Chain architectures that can form in solution micelles that have a network functionality greater than two are shown in black. (From Annable et al. 1993, with permission from the Journal of Rheology.)... 

For networked systems, each individual subsystem should be validated. After successful validation of the subsystems, network functions should be validated. The tests should be defined by a validation team that consists of expert members from various departments. 

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