Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data
Abstract Background Large-scale collaborative precision medicine initiatives (e.g., The Cancer Genome Atlas (TCGA)) are yielding rich multi-omics data. Integrative analyses of the resulting multi-omics data, such as somatic mutation, copy number alteration (CNA), DNA methylation, miRNA, gene express...
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| Main Authors: | , , , , |
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| Format: | Book |
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BMC,
2018-09-01T00:00:00Z.
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| Call Number: |
A1234.567 |
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| Copy 1 | Available |