Sentence examples for multiple similarity measures from inspiring English sources
The FRF method allows for multiple similarity measures and candidate genes in the model, and adaptively chooses the optimal similarity measure and disease-associated genes to reflect the underlying disease model.
Similarity fusion involves searching using multiple similarity measures.
Zhou et al[94] proposed a support vector machine (SVM -based SVM -basedatching algorithm to combine multiple spectralty matching.
The first type combines ranking from single searches based on multiple similarity measures, while the second one combines ranking from multiple searches based on a single similarity measure.
We hence conclude that a molecule is more likely to be active the more frequently it is retrieved when multiple similarity measures are available for carrying out a similarity search for a bioactive reference structure.
Other possible areas of study include the use of multiple similarity measures in the logistic regression model, accounting for individual judgements instead of using the majority decision, or the use of more sophisticated data fusion methods [22] than the simple consensus approach considered thus far.
SF involves searching a single reference structure against a database using multiple different similarity measures, and the output is obtained by combining the rankings resulting from these different measures.
The basis compounds method also allows us to easily take advantage of multiple complementary similarity measures by integrating them into one prediction model.
In human and Arabidopsis, the median and 75th percentile of LogFC scores of LogFC scores were higher than other measures, (b) and supplementary table S5 and S6 in Additional file 4), indicating that integrating multiple gene similarity measures with InteGO2 could increase the overall performance.
Compared to the pharmacological network models proposed by Cami et al., 11 the current study proposed a flexible computational framework to integrate arbitrary similarity measures from multiple sources, while Cami et al. directly generated several covariates as classification features by covariate definitions.
PREDICT is based on the observation that similar drugs are indicated for similar diseases, and utilizes multiple drug-drug and disease-disease similarity measures for the prediction task [ 13].
