Sentence examples for using an unsupervised clustering from inspiring English sources

A library of overlapping local structural prototypes was built using an unsupervised clustering approach called "hybrid protein model" (HPM).

In Stage 1, a set of clusters is identified using an unsupervised clustering method which is simultaneously applied to the training feature vectors extracted from the different classes.

First, all the spatial direction vectors d ( t, f ) = S x ( t, f ) S x ( t, f ), with (t f) ∈ Ω, are clustered by using an unsupervised clustering algorithm and taking into account that the number of sources is supposed to be known.

A heat map of over 6,000 differentially regulated genes was generated using an unsupervised clustering algorithm.

Consensus clustering, using an unsupervised clustering algorithm [ 17], was applied to the gene expression dataset to identify patients with similar overall expression profiles.

Using an unsupervised clustering algorithm, we identified probes with similar levels of differential DNA methylation in the CIMP+ and CIMP− samples across multiple tissues (see Additional file 2).

In a pilot study of acute meningitis, CSF spectra from small numbers of controls, patients with viral meningitis and bacterial/fungal meningitis were distinguished using an unsupervised cluster analysis method [8], suggesting that classification according to etiology is possible using larger data sets.

This was confirmed using an unsupervised cluster analysis: the expression profiles at the same time points from different regions were similar to one another and therefore clustered together compared to those from neighboring time points (Additional file 1 figure S3).

In contrast, Ezen-Can et al. (2015) have used an unsupervised clustering approach to gain an insight into the structure of forum posts in MOOCs.

To dissect the nature of the pathogen-associated proteins we next used an unsupervised clustering method based on 35 features (e.g. signal peptide prediction score, molecular weight, amino acid composition), deduced from the sequences.

To cluster the proteins according to the codon usage data we used an unsupervised clustering method analysis, SOM, which is a clustering method based on neural networks, and it helps to visualize datasets by mapping a high dimensional data space into a two dimensional space [ 26].