Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data

• Asıl Yazarlar: Yasser EL-Manzalawy (Yazar), Tsung-Yu Hsieh (Yazar), Manu Shivakumar (Yazar), Dokyoon Kim (Yazar), Vasant Honavar (Yazar)
• Materyal Türü: Kitap
• Baskı/Yayın Bilgisi: BMC, 2018-09-01T00:00:00Z.
• Konular: article
• Online Erişim: Connect to this object online.

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...