Significados de unsupervise clustering en inglés

Currently, most of the scRNA-seq data analyses are commenced with unsupervised clustering.

ANOVA and unsupervised clustering were used to identify gene expression profiles across disease states.

The intra- and inter-tumor heterogeneities of the profiles were compared with unsupervised clustering analysis.

Subclasses were identified by unsupervised clustering analysis.

Four patterns were revealed by unsupervised clustering analysis, one of them associated with significantly better prognosis than the others.

The clinical heterogeneity in the datasets was reduced by grouping the EDSS time series using an unsupervised clustering analysis.

Two groups of hyperdiploid samples were identified, on the basis of unsupervised clustering, which had an impact on overall survival.

The present study also highlights the power of unsupervised clustering methods to identify combinations of biomarkers for diagnosis and prognosis in medicine.

Unsupervised clustering of DNA methylation profiles revealed that malignant H3.3-mutated tumours are distinct from their benign counterpart, and other bone tumours.