Sentence examples for distinction between clusters from inspiring English sources

Despite the clear distinction between clusters based on nucleotides, no such distinction is found when comparing amino acid differences.

Whereas the distinction between clusters and fiat object parts is apparent, groups of material entities have a lot in common with fiat object parts.

The clustering quality is measured in terms of the density of the clusters, as well as the distinction between clusters and the closeness of the clusters to some reference clusters.

An important distinction between clusters 2 and 3 was their different profiles on the mental aspects of the disease, as cluster 2 clearly had lower levels of depression and anxiety than did cluster 3, despite cluster 2's having somewhat higher levels of pain, stiffness, dysfunction, sleep disturbance and fatigue.

The distinction between cluster types is not always clear-cut, and objects have been found that blur the lines between the categories.

Often, categories like 'anatomical cluster' and 'anatomical system' are introduced as basic categories (see e.g. Common Anatomy Reference Ontology, Version 1.5; Drosophila gross anatomy, Version 1.40; Teleost Anatomy Ontology, Version 1.205), which are comparable to the here proposed distinction between cluster and group.

Statistical analysis provided the distinction between three Clusters reflecting different hydrochemical processes.

Ranking the coefficients of the canonical discriminant analysis revealed those receptors, which contributed most to the distinction between the clusters in both dimensions.

Light scatter angles and fluorescence intensity measured in different channels allows the distinction between different clusters of cells with heterogeneous characteristics.

In standard high-field MR scanning on 1.5 3 T systems, on the contrary, the amygdala is imaged as a single, relatively homogenous portion of grey matter, therefore not allowing for a distinction between individual clusters.

A consecutive canonical discriminant analysis with 2 discriminating dimensions (x- and y-axes in Fig. 8 B ) revealed a most pronounced distinction between the clusters within the first dimension (x-axis; 72% explained variance), complemented by the distinction within the second dimension (y-axis; 28% explained variance).