Population of model

Wilson H. R., Cowan J. D. Excitatory and inhibitory interactions in localized populations of model neurons. Biophys J, 1972, 12,1-24. 

Variable selection is performed by using Genetic Algorithms (GA), based on the evolution of a population of models. In genetic algorithm terminology, the binary vector I is called a chromosome, which is a p-dimensional vector where each position (a gene) corresponds to a variable (1 if included in the model, 0 otherwise). Each chromosome represents a model with a subset of variables. 

Figure 12 Monotonic decreases in average crystallite size and crystallite population of model Ni/alumina during heating in steam at 973 K subsequent rapid change of particle size and population upon subsequent heating in...

It consists in the evolution of a population of models, i.e. a set of ranked models according to some objective function, based on the crossover and mutation processes, which are alternatively repeated until a stop condition is encountered (e.g., a user-defined maximum number of iterations) or the process is ended arbitrarily. 

Variable subset selection is performed by GAs, optimising populations of models according to a defined objective function related to model quality. In partial ranking models objective function is an expression of the degree of agreement between the element ranking resulting from experimental attributes and that provided by the selected subset of model attributes. 

Britton OJ, Bueno-Orovio A, Van Ammel K, Ln HR, Towart R, Gallacher DJ, Rodriguez B (2013). Experimentally calibrated population of models predicts and explains intersnbject variability in cardiac cellular electrophysiology. Proc Natl Acad Sci USA 110 E2098-E2105. 

Genetic algorithms start by creating a population of models. Recombination operations between pairs of parent models occur more frequently for those that have a high fitness score. If the fitness score of a newly generated model is... 

In this application, each generation is a population of models containing a discrete set of components or basis functions. To specify a linear model completely, all one needs is the set of independent variables used, which in this case are the basis functions. The coefficients of the various terms in the model are dependent on the data set used. However, given a data set and the set of basis functions these can be determined by linear regression. Thus, an individual in the population can be represented completely by specifying the chosen set of basis functions. Figure 11 shows an example of a population of models derived from a set of basis functions. 

Evolution of receptor models. After an initial population of models is generated and evaluated, parents (the initial models) are selected in a fitness-weighted random manner. Thus, any member of the population may be selected, but members with higher fitness are more likely to be chosen. The result is that good partial solutions to the problem may be combined with other good partial solutions to produce even better models. 

The ranking of conformational free energies indicated that the closed state of cAPK is favored even in the absence of ligands, which is in contrast to experimental data that showed a preferred population of the open conformation. One reason for this discrepancy could be that the modelled intermediate ... 

The A and B coefficients can be used in a kinetic equation model to follow the time evolution of the populations of the corresponding levels ... 

Measuring Protein Sta.bihty, Protein stabihty is usually measured quantitatively as the difference in free energy between the folded and unfolded states of the protein. These states are most commonly measured using spectroscopic techniques, such as circular dichroic spectroscopy, fluorescence (generally tryptophan fluorescence) spectroscopy, nmr spectroscopy, and absorbance spectroscopy (10). For most monomeric proteins, the two-state model of protein folding can be invoked. This model states that under equihbrium conditions, the vast majority of the protein molecules in a solution exist in either the folded (native) or unfolded (denatured) state. Any kinetic intermediates that might exist on the pathway between folded and unfolded states do not accumulate to any significant extent under equihbrium conditions (39). In other words, under any set of solution conditions, at equihbrium the entire population of protein molecules can be accounted for by the mole fraction of denatured protein, and the mole fraction of native protein,, ie. 

Many different types of models are used as the foundation for statistical analysis. These models are also referred to as populations. 

The energy laws of Bond, Kick, and Rittinger relate to grinding from some average feed size to some product size but do not take into account the behavior of different sizes of particles in the mill. Computer simulation, based on population-balance models [Bass, Z. Angew. Math. Phys., 5(4), 283 (1954)], traces the breakage of each size of particle as a function of grinding time. Furthermore, the simu-... 

The coalescence-redispersion (CRD) model was originally proposed by Curl (1963). It is based on imagining a chemical reactor as a number population of droplets that behave as individual batch reactors. These droplets coalesce (mix) in pairs at random, homogenize their concentration and redisperse. The mixing parameter in this model is the average number of collisions that a droplet undergoes. 

Now the speeial utility of the MSMPR population balanee model equation at steady state ean be elearly seen. Firstly, at known residenee time, t, the Growth rate, G, may be obtained from the slope (= —1/Gt) of the plot in Figure 3.7. 

PC-based models are presented for evaluating diesel unavailability. Parameters for the models are discussed in the report, but individual DG unavailability events are not listed. Generic TIs for a range of parameters and population of plants are displayed. 

Combinations of weather conditions, wind speed and wind direction along witli boiling point, vapor density, diffusivity, and heat of vaporization of tlie chemical released vary the healtli impact of tlie released chemical on the nearby population. To model a runaway reaction, the release of 10,000 gallons was assumed to occur over a 15-minute period. Tlie concentration of the chemical released was estimated, using procedures described in Part III (Chapter 12) for each combination of weather condition, wind speed, and wind direction. The results, combined with population data for tlie area adjacent to tlie plant, led to probability estimates of the number of people affected. Table 21.5.3 sunimarizes tlie findings. 

FIGURE 15.9 Monod-Wyman-Changeux (MWC) model for allosteric transitions. Consider a dimeric protein that can exist in either of two conformational states, R or T. Each subunit in the dimer has a binding site for substrate S and an allosteric effector site, F. The promoters are symmetrically related to one another in the protein, and symmetry is conserved regardless of the conformational state of the protein. The different states of the protein, with or without bound ligand, are linked to one another through the various equilibria. Thus, the relative population of protein molecules in the R or T state is a function of these equilibria and the concentration of the various ligands, substrate (S), and effectors (which bind at f- or Fj ). As [S] is increased, the T/R equilibrium shifts in favor of an increased proportion of R-conformers in the total population (that is, more protein molecules in the R conformational state). 

For either experiment we can consider that irradiated protons to flip back and forth between their two spin-states so rapidly that they no longer couple with other protons in the same molecule. An alternative rationale can be couched in terms of the decoupling field equalizing the populations of the two energy levels of the irradiated protons, which is qualitatively equivalent to saturating that resonance. (Although neither of these two models is strictly correct, they do at least provide a simple rationale for the N.M.D.R. experiment.)... 

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