Article

BiCoN: Network-constrained biclustering of patients and omics data

2020-02-03

Abstract excerpt

<h4>Motivation</h4> Unsupervised learning approaches are frequently employed to identify patient subgroups and biomarkers such as disease-associated genes. Thus, clustering and biclustering are powerful techniques often used with expression data, but are usually not suitable to unravel molecular mechanisms along with patient subgroups. To alleviate this, we developed the network-constrained biclustering approach...

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Literature Corpus work: f0b0eeac-efbe-5f31-b6d3-87989c5ca9db
DOI: 10.1101/2020.01.31.926345

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