CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
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Comprehensive Cross-Population Analysis of High-Grade Serous Ovarian Cancer Supports No More Than Three Subtypes.Challenges and Opportunities in Studying the Epidemiology of Ovarian Cancer Subtypes.Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters.Cancer Subtype Discovery Using Prognosis-Enhanced Neural Network Classifier in Multigenomic Data
P2860
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
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
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
@ast
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
@en
type
label
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
@ast
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
@en
prefLabel
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
@ast
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.
@en
P2860
P1433
P1476
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets
@en
P2093
Catherine R Planey
Olivier Gevaert
P2860
P2888
P356
10.1186/S13073-016-0281-4
P577
2016-03-09T00:00:00Z
P5875
P6179
1007877207