A probabilistic framework for peptide and protein quantification from data-dependent and data-independent LC-MS proteomics experiments.
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OLFM4, KNG1 and Sec24C identified by proteomics and immunohistochemistry as potential markers of early colorectal cancer stages.A review on recent developments in mass spectrometry instrumentation and quantitative tools advancing bacterial proteomics.Bioinformatics challenges and solutions in proteomics as quantitative methods mature.Specificity of the osmotic stress response in Candida albicans highlighted by quantitative proteomics
P2860
A probabilistic framework for peptide and protein quantification from data-dependent and data-independent LC-MS proteomics experiments.
description
2012 nî lūn-bûn
@nan
2012 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
A probabilistic framework for ...... LC-MS proteomics experiments.
@ast
A probabilistic framework for ...... LC-MS proteomics experiments.
@en
A probabilistic framework for ...... LC-MS proteomics experiments.
@nl
type
label
A probabilistic framework for ...... LC-MS proteomics experiments.
@ast
A probabilistic framework for ...... LC-MS proteomics experiments.
@en
A probabilistic framework for ...... LC-MS proteomics experiments.
@nl
prefLabel
A probabilistic framework for ...... LC-MS proteomics experiments.
@ast
A probabilistic framework for ...... LC-MS proteomics experiments.
@en
A probabilistic framework for ...... LC-MS proteomics experiments.
@nl
P2093
P2860
P50
P356
P1476
A probabilistic framework for ...... LC-MS proteomics experiments.
@en
P2093
Chris Hughes
Hye Ryung Jung
Jacek Sikora
James I Langridge
Johannes P C Vissers
John Skilling
Keith Richardson
Richard Denny
Ronald Melki
Virginie Redeker
P2860
P304
P356
10.1089/OMI.2012.0019
P577
2012-08-07T00:00:00Z