Self Correcting Nanoflow LC-MS for Clinical Proteomics
Self Correcting Nanoflow LC-MS for Clinical Proteomics
批准号:
8840976
负责人:
Michael MacCoss
金额:
$37.43万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2016-04-30
关键词:
BiologicalBiological AssayClinicalCommunitiesComputer softwareCouplesDataData CollectionData QualityDevelopmentDiseaseEnvironmentEventFailureGeneticGoalsHealthInformation SystemsLaboratoriesLiquid ChromatographyLiquid substanceMachine LearningMass Spectrum AnalysisMeasurementMedicineMethodsOutcomePeptidesPerformancePharmaceutical PreparationsPost-Translational Protein ProcessingProcessProtein AnalysisProteinsProteomicsProtocols documentationQuality ControlReproducibilityRoboticsRunningSamplingSourceSystemTechnologyTimeTrainingUniversitiesWashingtonbasecomparativecomplex biological systemsexperienceimprovedinstrumentliquid chromatography mass spectrometrymass spectrometernovelopen sourceoperationprotein protein interactionresponsetool
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): The overall goal of this proposal is to improve the quality, reliability, and interlaboratory comparability of peptide mass spectrometry data. Mass spectrometry (MS) has become a fundamental technology for the identification and quantitative analysis of proteins, protein interactions, and protein post-translational modifications. These analyses are an important part of solving biological problems that involve changes in protein abundance in response to disease, drug treatment, and genetic or environmental perturbations. Unfortunately, the application of protein mass spectrometry measurements in the clinical laboratory has been limited. Unlike most clinical assays by mass spectrometry, which use microflow liquid chromatography, peptide measurements are commonly performed using a nanoflow liquid chromatograph interface to the mass spectrometer (nanoflow LC-MS). Despite their analytical power, these nanoflow LC-MS methods have been difficult to apply robustly in quantitative assays involving large numbers of samples from a challenging sample matrix. The successful completion of our project will result in a peptide analysis platform that can automatically assess problems with the nanoflow LC-MS system and correct the problem during an analytical run and will significantly improve the robustness and reproducibility of peptide mass spectrometry measurements.
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批准号:10189938
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批准号:10573256
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资助金额:$48.48万
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财政年份:2020
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资助金额:$314.46万
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依托单位:
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批准号:10573245
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资助金额:$5.64万
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批准号:10359187
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资助金额:$314.46万
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财政年份:2020
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批准号:10359188
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财政年份:2020
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批准号:10579223
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财政年份:2019
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负责人:Michael MacCoss
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依托单位:
The biofilm matrix of P. aeruginosa
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批准号:10330563
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资助金额:$56.71万
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财政年份:2019
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负责人:Michael MacCoss
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依托单位:
The Chorus Project: A Sustainable Cloud Solution for Mass Spectrometry Data
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财政年份:2017
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负责人:Michael MacCoss
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依托单位:
Systematic and Comprehensive Sampling of Peptides in Mixtures by Tandem Mass Spectrometry
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批准号:8850241
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项目类别:
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资助金额:$19.38万
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财政年份:2015
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负责人:Michael MacCoss
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依托单位:
Systematic and Comprehensive Sampling of Peptides in Mixtures by Tandem Mass Spectrometry
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批准号:9052745
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项目类别:
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资助金额:$22.73万
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财政年份:2015
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负责人:Michael MacCoss
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依托单位:
Self Correcting Nanoflow LC-MS for Clinical Proteomics
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批准号:8558710
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项目类别:
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资助金额:$35.59万
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财政年份:2013
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负责人:Michael MacCoss
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依托单位:
Skyline Targeted Proteomics Environment
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批准号:8217996
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项目类别:
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资助金额:$37.98万
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财政年份:2011
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负责人:Michael MacCoss
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依托单位:
Skyline Targeted Proteomics Environment
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批准号:8915218
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项目类别:
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资助金额:$38.63万
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财政年份:2011
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负责人:Michael MacCoss
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依托单位:
Skyline Targeted Proteomics Environment
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批准号:8539058
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项目类别:
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资助金额:$37.27万
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财政年份:2011
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负责人:Michael MacCoss
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DEVELOPMENT OF CUSTOM FAIMS ELECTRONICS
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批准号:8365834
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项目类别:
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资助金额:$0.95万
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财政年份:2011
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负责人:Michael MacCoss
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依托单位:
OPTIMIZATION OF NANOFLOW LC FOR IMPROVED PEAK CAPACITY AND PEPTIDE IDS
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批准号:8365816
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项目类别:
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资助金额:$0.95万
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财政年份:2011
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负责人:Michael MacCoss
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依托单位:
海外基金