Sentence examples for classification by clusters from inspiring English sources

Unigene classification by clusters of orthologous groups function.

This way of illustration helps to judge the correctness of our initial classification, and the classification by cluster analysis.

The sensitivity for the control class was relatively lower, especially in classification by clustering, when compared with that for the other two classes.

That was because clustering of markers was very stable with the large number of tumors (i.e., excluding a few tumors did not substantially influence results) while tumor classification by clustering analysis based on the 16 markers was not stable.

This cross validation study examined the reliability of the Multidimensional Pain Inventory (MPI) and the stability of the Multidimensional Pain Inventory Classification System of the empirically derived subgroup classification obtained by cluster analysis in chronic musculoskeletal pain.

To overcome this rigidity, we performed a more flexible classification by hierarchical clustering of 159 patients using the 64-gene set; here the risk score was only used for a description of the resulting clusters.

Classification by other peak clusters also generated high diagnostic accuracy (95%) with substantial diagnostic potential (Figure S6).

To test this hypothesis on the 724 analytes we tried to identify analyte groups characterized by similar, yet distant and reproducible distributions using a marker-'free'-based classification by k-medoids clustering, allowing only the cytosolic compartment to be partitioned into different clusters without being assigned to another compartment.

After refinement of the initial classification by non-hierarchical cluster analysis, 8.6%% of the respondents changed subgroup.

Starting in the 1950s, taxonomists began to incorporate computers into their work, using the machines to assist in the classification of organisms by clustering them based on similarities of sets of traits.

In the 1950s taxonomists began to incorporate computers into their work, using the machines to assist in the classification of organisms by clustering them on the basis of similarities of sets of traits.