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The denoised dataset was clustered into operational taxonomic units (OTUs) with 97% similarity threshold, using the UCLUST algorithm.

The combined, redundant dataset was clustered using CD-HIT [23].

The same NSCLC dataset was clustered into 4 subgroups by these methods.

Finally, the combined dataset was clustered using an average linkage algorithm based on Pearson correlation coefficients.

Each breast cancer dataset was clustered separately with the gene sets specific for each of the 10 fibrous tumor signatures.

However, the only one strain AY964114_04_US_25259_Dog of the RL genotype in the 176-sequences dataset was clustered with the Asia-4 genotype in the BMCMC tree (Fig.  3) and with the EW genotype in the NJ tree (Additional file 2).

Districts in the dataset are clustered into 3 clusters using CLARA algorithm.

Figure 5 The COX-2 dataset is clustered into 7 clusters.

Finally, the Level 1 scaffolds for each dataset were clustered and visualized by Tree Maps.

Next, the training dataset is clustered by the DBSCAN to select the representative data for the ENNs.

The Level 1 scaffolds for each dataset were clustered by their fingerprint similarity using the ECFP_6 fingerprints.