about
Visualization of proteomics data using R and bioconductorCardiovascular proteomics in the era of big data: experimental and computational advancesMass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata.Detecting Significant Changes in Protein AbundanceMaxReport: An Enhanced Proteomic Result Reporting Tool for MaxQuantAn overview of innovations and industrial solutions in Protein Microarray Technology.Computational quality control tools for mass spectrometry proteomics.Integrative Analysis of Proteomics Data to Obtain Clinically Relevant Markers.GiaPronto: a one-click graph visualization software for proteomics datasets.Designing Successful Proteomics Experiments.A Bioconductor workflow for processing and analysing spatial proteomics data
P2860
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P2860
description
2013 nî lūn-bûn
@nan
2013 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Using R and Bioconductor for proteomics data analysis.
@ast
Using R and Bioconductor for proteomics data analysis.
@en
type
label
Using R and Bioconductor for proteomics data analysis.
@ast
Using R and Bioconductor for proteomics data analysis.
@en
prefLabel
Using R and Bioconductor for proteomics data analysis.
@ast
Using R and Bioconductor for proteomics data analysis.
@en
P1476
Using R and Bioconductor for proteomics data analysis.
@en
P2093
Andy Christoforou
P356
10.1016/J.BBAPAP.2013.04.032
P407
P433
P577
2013-05-18T00:00:00Z