2022
TidyMass an object-oriented reproducible analysis framework for LC–MS data
Shen X, Yan H, Wang C, Gao P, Johnson CH, Snyder MP. TidyMass an object-oriented reproducible analysis framework for LC–MS data. Nature Communications 2022, 13: 4365. PMID: 35902589, PMCID: PMC9334349, DOI: 10.1038/s41467-022-32155-w.Peer-Reviewed Original ResearchMeSH KeywordsChromatography, LiquidEcosystemMetabolomicsReproducibility of ResultsSoftwareTandem Mass SpectrometryWorkflowConceptsObject-oriented computational frameworkComputational frameworkExtensible toolMetabolomics data analysisData structureWorkflow needsModular architectureOwn pipelinesData processingMultiple toolsAnalysis frameworkDesign philosophyR packageFrameworkLC-MS dataData analysisToolUsersArchitectureTraceabilityPipelineProcessingPackageGrammar
2020
Analyzing Metabolomics Data for Environmental Health and Exposome Research
Cai Y, Rosen Vollmar AK, Johnson CH. Analyzing Metabolomics Data for Environmental Health and Exposome Research. Methods In Molecular Biology 2020, 2104: 447-467. PMID: 31953830, DOI: 10.1007/978-1-0716-0239-3_22.Peer-Reviewed Original ResearchMeSH KeywordsChromatography, LiquidData AnalysisEnvironmental ExposureEnvironmental HealthExposomeMass SpectrometryMetabolomicsResearchRisk AssessmentConceptsLiquid chromatography-mass spectrometryChromatography-mass spectrometryBiological samplesExposure chemicalsExternal exposureSimultaneous analysisExposome researchHealth outcomesDisease preventionUnique advantagesBiological responsesUntargeted metabolomicsExposure risk assessmentHost susceptibilityMetabolomics technologyExposomeMetabolomic analysisRecent advancesSpectrometryExposureUntargeted metabolomics dataMetabolomicsHuman healthMetabolomics dataCumulative measure
2014
Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling
Benton HP, Ivanisevic J, Mahieu NG, Kurczy ME, Johnson CH, Franco L, Rinehart D, Valentine E, Gowda H, Ubhi BK, Tautenhahn R, Gieschen A, Fields MW, Patti GJ, Siuzdak G. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling. Analytical Chemistry 2014, 87: 884-891. PMID: 25496351, PMCID: PMC4303330, DOI: 10.1021/ac5025649.Peer-Reviewed Original ResearchMeSH KeywordsChromatography, LiquidComputational BiologyDatabases, FactualDesulfovibrio vulgarisElectronic Data ProcessingMetabolomicsSoftwareTandem Mass SpectrometryConceptsMass spectrometry data acquisitionSystems biology levelMass spectrometry analysisBioinformatics resourcesGlobal profilingTandem mass spectrometry dataProfiling datasetsMass spectrometry databaseMass spectrometry dataSpectrometry analysisProfilingData acquisitionSpectrometry dataRapid metabolite identificationMetabolomic profilingUntargeted metabolomicsBacterial samplesMetabolomicsSimultaneous data processingIdentificationMetabolite identificationMetabolomics workflowsFliesAutomatic searchAutonomous approach
2013
Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database
Zhu ZJ, Schultz AW, Wang J, Johnson CH, Yannone SM, Patti GJ, Siuzdak G. Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database. Nature Protocols 2013, 8: 451-460. PMID: 23391889, PMCID: PMC3666335, DOI: 10.1038/nprot.2013.004.Peer-Reviewed Original ResearchMeSH KeywordsChromatography, LiquidComputational BiologyDatabases, FactualMass SpectrometryMetabolomicsSoftwareConceptsLiquid chromatography-quadrupole timeProfiling experimentsMETLIN metabolite databaseMore populationsSeven-step protocolFlight mass spectrometry characterizationMost biological samplesFlight mass spectrometryMass spectrometry characterizationTandem MSMetabolomic featuresQuadrupole timeComprehensive platformUntargeted metabolomicsMass spectrometryMS dataMETLIN databaseLC-Q-TOFMetabolitesMetabolite databasesBiological samplesThousands of peaks