(Q34635691)

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Improving the success rate of proteome analysis by modeling protein-abundance distributions and experimental designs

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scholarly article

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Europe PubMed Central

3 August 2017

Improving the success rate of proteome analysis by modeling protein-abundance distributions and experimental designs (English)

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Europe PubMed Central

3 August 2017

author name string

Jan Eriksson

1

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3 August 2017

David Fenyö

2

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3 August 2017

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1 June 2007

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3 August 2017

Nature Biotechnology

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3 August 2017

25

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3 August 2017

651-655

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3 August 2017

6

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Europe PubMed Central

3 August 2017

https://scigraph.springernature.com/pub.10.1038/nbt1315

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Global analysis of protein expression in yeast

1 reference

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The human plasma proteome: history, character, and diagnostic prospects

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Mass spectrometry-based proteomics

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Intact-protein-based High-resolution Three-dimensional Quantitative Analysis System for Proteome Profiling of Biological Fluids

1 reference

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Proteomic LC-MS systems using nanoscale liquid chromatography with tandem mass spectrometry

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Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification.

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Tandem mass spectrometry for peptide and protein sequence analysis

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Identifying the proteome: software tools

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Informatics for protein identification by mass spectrometry

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A statistical basis for testing the significance of mass spectrometric protein identification results

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Probity: a protein identification algorithm with accurate assignment of the statistical significance of the results.

1 reference

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An improved model for prediction of retention times of tryptic peptides in ion pair reversed-phase HPLC: its application to protein peptide mapping by off-line HPLC-MALDI MS.

1 reference

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7 January 2021

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10.1038/NBT1315

1 reference

Europe PubMed Central

3 August 2017

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1 reference

Europe PubMed Central

3 August 2017

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