Article

The usefulness of sparse k-means in metabolomics data: An example from breast cancer data

2022-02-08

Abstract excerpt

In processing metabolomics data, multidimensional quantitative data from thousands of metabolites are often sparse, that is, only a small fraction of metabolites are relevant to the phenotype of interest. Clustering is therefore used to discover subtypes from omics data. Sparse processing, which selects important metabolites from the total omics data, is an effective clustering technique. This study investigated t...

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Literature Corpus work: 1d9ff58e-527b-53fe-9693-b351d81ae4f1
DOI: 10.1101/2022.02.05.479235

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