MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
about
Machine learning for epigenetics and future medical applications.Statistical and integrative system-level analysis of DNA methylation data.MethCNA: a database for integrating genomic and epigenomic data in human cancer.BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation referenceEpigenome-Wide Analyses Identify Two Novel Associations With Recurrent Stroke in the Vitamin Intervention for Stroke Prevention Clinical Trial
P2860
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
description
2017 nî lūn-bûn
@nan
2017年の論文
@ja
2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
2017年论文
@zh
2017年论文
@zh-cn
name
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
@en
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
@nl
type
label
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
@en
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
@nl
prefLabel
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
@en
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
@nl
P2093
P2860
P1433
P1476
MeDeCom: discovery and quantification of latent components of heterogeneous methylomes
@en
P2093
Gilles Gasparoni
Martin Slawski
Matthias Hein
Nikita Vedeneev
Pavlo Lutsik
P2860
P2888
P356
10.1186/S13059-017-1182-6
P50
P577
2017-03-24T00:00:00Z
P6179
1084252046