Using knowledge-driven genomic interactions for multi-omics data analysis: metadimensional models for predicting clinical outcomes in ovarian carcinoma.
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Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancerIdentifying subtype-specific associations between gene expression and DNA methylation profiles in breast cancerMore Is Better: Recent Progress in Multi-Omics Data Integration MethodsMin-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics dataIntegrative pathway-based survival prediction utilizing the interaction between gene expression and DNA methylation in breast cancerPathway-based subnetworks enable cross-disease biomarker discovery
P2860
Using knowledge-driven genomic interactions for multi-omics data analysis: metadimensional models for predicting clinical outcomes in ovarian carcinoma.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Using knowledge-driven genomic ...... outcomes in ovarian carcinoma.
@ast
Using knowledge-driven genomic ...... outcomes in ovarian carcinoma.
@en
type
label
Using knowledge-driven genomic ...... outcomes in ovarian carcinoma.
@ast
Using knowledge-driven genomic ...... outcomes in ovarian carcinoma.
@en
prefLabel
Using knowledge-driven genomic ...... outcomes in ovarian carcinoma.
@ast
Using knowledge-driven genomic ...... outcomes in ovarian carcinoma.
@en
P2093
P2860
P356
P1476
Using knowledge-driven genomic ...... outcomes in ovarian carcinoma.
@en
P2093
Anastasia Lucas
Dokyoon Kim
Ruowang Li
Scott M Dudek
Shefali S Verma
P2860
P304
P356
10.1093/JAMIA/OCW165
P577
2017-05-01T00:00:00Z