Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).
about
Technical advances in proteomics: new developments in data-independent acquisitionEmerging proteomic technologies for elucidating context-dependent cellular signaling events: A big challenge of tiny proportionsIon Activation Methods for Peptides and ProteinsDeMix-Q: Quantification-Centered Data Processing Workflow.Intelligent data acquisition blends targeted and discovery methods.DeMix workflow for efficient identification of cofragmented peptides in high resolution data-dependent tandem mass spectrometry.Whole cell, label free protein quantitation with data independent acquisition: quantitation at the MS2 level.Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues.Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass SpectrometryMapping Biological Networks from Quantitative Data-Independent Acquisition Mass Spectrometry: Data to Knowledge Pipelines.Fast MS/MS acquisition without dynamic exclusion enables precise and accurate quantification of proteome by MS/MS fragment intensityLocus-specific Retention Predictor (LsRP): A Peptide Retention Time Predictor Developed for Precision Proteomics.Role of phosphoproteomics in the development of personalized cancer therapies.Optimized experimental workflow for tandem mass spectrometry molecular networking in metabolomics.Approaches to identify kinase dependencies in cancer signalling networks.Targeted Annotation of S-Sulfonylated Peptides by Selective Infrared Multiphoton Dissociation Mass Spectrometry.Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS).Development of Selected Reaction Monitoring Methods to Systematically Quantify Kinase Abundance and Phosphorylation Stoichiometry in Human Samples.A mass spectrometry-based proteomic analysis of Homer2-interacting proteins in the mouse brain.On the Reproducibility of Label-Free Quantitative Cross-Linking/Mass Spectrometry.Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells.
P2860
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P2860
Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).
description
2013 nî lūn-bûn
@nan
2013 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հուլիսին 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
Maximizing peptide identificat ...... a-dependent acquisition (DDA).
@ast
Maximizing peptide identificat ...... a-dependent acquisition (DDA).
@en
type
label
Maximizing peptide identificat ...... a-dependent acquisition (DDA).
@ast
Maximizing peptide identificat ...... a-dependent acquisition (DDA).
@en
prefLabel
Maximizing peptide identificat ...... a-dependent acquisition (DDA).
@ast
Maximizing peptide identificat ...... a-dependent acquisition (DDA).
@en
P2093
P2860
P356
P1476
Maximizing peptide identificat ...... a-dependent acquisition (DDA).
@en
P2093
Avinash K Gadok
Christine C Wu
Karen K Szumlinski
Nicholas J Shulman
Nicholas W Bateman
Scott P Goulding
P2860
P304
P356
10.1074/MCP.M112.026500
P577
2013-07-02T00:00:00Z