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...
Bewaard in:
| Hoofdauteurs: | , , , , |
|---|---|
| Formaat: | Boek |
| Gepubliceerd in: |
BMC,
2018-09-01T00:00:00Z.
|
| Onderwerpen: | |
| Online toegang: | Connect to this object online. |
| Tags: |
Voeg label toe
Geen labels, Wees de eerste die dit record labelt!
|
Internet
Connect to this object online.3rd Floor Main Library
| Plaatsingsnummer: |
A1234.567 |
|---|---|
| Kopie 1 | Beschikbaar |