Improving peak detection in high-resolution LC/MS metabolomics data using preexisting knowledge and machine learning approach.
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Local false discovery rate estimation using feature reliability in LC/MS metabolomics dataHigh-resolution metabolomics of occupational exposure to trichloroethyleneComputational Metabolomics: A Framework for the Million Metabolome.Updates in metabolomics tools and resources: 2014-2015.High-Resolution Metabolomics Assessment of Military Personnel: Evaluating Analytical Strategies for Chemical Detection.Particulate metal exposures induce plasma metabolome changes in a commuter panel study
P2860
Improving peak detection in high-resolution LC/MS metabolomics data using preexisting knowledge and machine learning approach.
description
2014 nî lūn-bûn
@nan
2014 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Improving peak detection in hi ...... and machine learning approach.
@ast
Improving peak detection in hi ...... and machine learning approach.
@en
type
label
Improving peak detection in hi ...... and machine learning approach.
@ast
Improving peak detection in hi ...... and machine learning approach.
@en
prefLabel
Improving peak detection in hi ...... and machine learning approach.
@ast
Improving peak detection in hi ...... and machine learning approach.
@en
P2860
P356
P1433
P1476
Improving peak detection in hi ...... and machine learning approach.
@en
P2093
Dean P Jones
Tianwei Yu
P2860
P304
P356
10.1093/BIOINFORMATICS/BTU430
P407
P577
2014-07-07T00:00:00Z