Phenotype prediction based on genome-wide DNA methylation data.
about
Prediction of cancer proteins by integrating protein interaction, domain frequency, and domain interaction data using machine learning algorithms.Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation.Beyond protein expression, MOPED goes multi-omicsViralEpi v1.0: a high-throughput spectrum of viral epigenomic methylation profiles from diverse diseases.Evaluation of variable selection methods for random forests and omics data sets.Ratiometric Array of Conjugated Polymers-Fluorescent Protein Provides a Robust Mammalian Cell Sensor.A deep neural network based regression model for triglyceride concentrations prediction using epigenome-wide DNA methylation profiles
P2860
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P2860
Phenotype prediction based on genome-wide DNA methylation data.
description
2014 nî lūn-bûn
@nan
2014 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年学术文章
@wuu
2014年学术文章
@zh-cn
2014年学术文章
@zh-hans
2014年学术文章
@zh-my
2014年学术文章
@zh-sg
2014年學術文章
@yue
name
Phenotype prediction based on genome-wide DNA methylation data.
@ast
Phenotype prediction based on genome-wide DNA methylation data.
@en
type
label
Phenotype prediction based on genome-wide DNA methylation data.
@ast
Phenotype prediction based on genome-wide DNA methylation data.
@en
prefLabel
Phenotype prediction based on genome-wide DNA methylation data.
@ast
Phenotype prediction based on genome-wide DNA methylation data.
@en
P2860
P356
P1433
P1476
Phenotype prediction based on genome-wide DNA methylation data.
@en
P2093
Thomas Wilhelm
P2860
P2888
P356
10.1186/1471-2105-15-193
P577
2014-06-17T00:00:00Z
P5875
P6179
1028350309