Fitness score

Fig. 15.25 Partial display of virtual screen of conformational ensemble of " 75 000 structure library based on multiple templates. A display of fitness scores to a three-point pharmacophore model provides initial signs of similarity of a library design to that model. Subsequent virtual screening against a more stringent four-point pharmacophore model further highlights potentially useful library designs.

When screening our database for potential targets of biotin, 7 out of the 10 streptavidin entries present in the sc-PDB were ranked at the top eight positions with very good averaged fitness scores (Fig. 9). Interestingly, the... 

Here the word good and goodness are strictly related to the binary classification that a product is good only if it fits all the multi-objective criteria. GLARE could easily be adapted to work with a scalar fitness score. 

Cause c Fitting scored by silica packing left in threads. 

Fig. 15.4 Performance assessment with ROC curves. The theoretical distributions for active (red curve) and inactive compounds (blue) as a function of their fit score on the pharmacophore (left). In most cases, these distributions overlap, leading to false predictions (colored areas). Upon threshold modification, proportions of such erroneous classifications change dramatically. Hence to any selection threshold S corresponds a unique...

In GA, fitness function is defined to measure the fitness of each individual chromosome so as to determine which will reproduce and survive into the next generation. Thus, given a particular chromosome, the fitness function returns a single numerical score, fitness , which is proportional to the ability of the individual that the chromosome represents. The fitness score assigned to each individual in the population depends on how well that individual solves a specific problem. In this line... 

This score is used in situations where one graph is matched with a set of graphs to select the best match. To calculate the fitness score, we apply (18.3) to SG where... 

The function taxdist (C C,+ i) is the taxonomic (or semantics) distance [11] between two concepts Ci and C,+i. We calculate the taxonomic distance between two concepts as the minimum number of taxonomic edges that needs to be traversed to reach C from C +i. After transformations have been applied, SG is returned along with a numeric score reflecting the fitness of the match between Gi, G2,..., G . This score is computed based on the number of matched triples over the size of the graphs being matched [13]. The fitness score is also computed using a simple formula as given by (18.5). In our example, the fitness of SG is approximately 0.5. 

Fitness computation and ranking Evaluate each candidate expression in the population using training input-output data and determine its fitness score using the preselected fitness function rank the expressions in the order of their decreasing fitness scores. 

Selection From the ranked population, create a parent pool of candidate solutions with high fitness scores using selection methods such as Roulette-wheel selection , tournament selection , elitist mutation , etc. 

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