05000nam 2201321z- 450 991055735440332120220111(CKB)5400000000042346(oapen)https://directory.doabooks.org/handle/20.500.12854/76855(oapen)doab76855(EXLCZ)99540000000004234620202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierMetabolomics Data Processing and Data Analysis-Current Best PracticesBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (276 p.)3-0365-1194-6 3-0365-1195-4 Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme "Best Practices in Metabolomics Data Analysis". Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows.Research & information: generalbicsscall ion fragmentationbiostatisticsbootstrapped-VIPchemical classificationcombinatorial fragmentationcompound identificationcomputational metabolomicscomputational statisticalconstraint-based modelingdata processingdata repositorydata-dependent acquisition (DDA)data-independent acquisitiondisease riskenrichment analysisenvironmental factorsexperimental designflux balanceforensicsfragmentation (MS/MS)full-scan MS/MS processinggenome-scale metabolic modelingglobal metabolomicsgut microbiomehost-microbiomein silicoin silico workflowsion selection algorithmsLC-MSLC-MSlipidomicsliquid chromatographyliquid chromatography high-resolution mass spectrometryliquid chromatography mass spectrometryliquid chromatography-mass spectrometry (LC-MS)liquid chromatography-mass spectrometry (LC/MS)mass spectral librariesmass spectrometrymass spectrometry imagingmeta-omicsmetabolic networksmetabolic pathway and network analysismetabolic profilingmetabolic reconstructionsmetabolismmetabolite annotationmetabolite identificationmetabolome miningmetabolomicsmetabolomics data mappingmetabolomics imagingmetagenomicsmolecular familiesMS spectral predictionmultivariate risk modelingnetworkingnontarget analysisNPLSpathway analysisPLSR programmingR-MetaboList 2reanalysisrule-based fragmentationsample preparationsimulatorspectra processingstructure-based chemical classificationsubstructuressupervised learningtandem mass spectral librarytargeted analysistime seriestriplotunivariate and multivariate statisticsunsupervised learninguntargeted analysisuntargeted metabolomicsvariable selectionwastewaterResearch & information: generalHanhineva Katiedt1328811Van der Hooft JustinedtHanhineva KatiothVan der Hooft JustinothBOOK9910557354403321Metabolomics Data Processing and Data Analysis-Current Best Practices4416432UNINA