BiCoN: Network-constrained biclustering of patients and omics data
Motivation: Unsupervised learning approaches are frequently used to stratify patients into clinically relevant subgroups and to identify biomarkers such as disease-associated genes. However, clustering and biclustering techniques are oblivious to the functional relationship of genes and are thus not...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Oxford University Press
2021
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| Online Access: | View Fulltext in Publisher |