LEADER 04999nam 2201309z- 450 001 9910557354403321 005 20231214133335.0 035 $a(CKB)5400000000042346 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76855 035 $a(EXLCZ)995400000000042346 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMetabolomics Data Processing and Data Analysis?Current Best Practices 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 electronic resource (276 p.) 311 $a3-0365-1194-6 311 $a3-0365-1195-4 330 $aMetabolomics 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. 606 $aResearch & information: general$2bicssc 610 $ametabolic networks 610 $amass spectral libraries 610 $ametabolite annotation 610 $ametabolomics data mapping 610 $anontarget analysis 610 $aliquid chromatography mass spectrometry 610 $acompound identification 610 $atandem mass spectral library 610 $aforensics 610 $awastewater 610 $agut microbiome 610 $ameta-omics 610 $ametagenomics 610 $ametabolomics 610 $ametabolic reconstructions 610 $agenome-scale metabolic modeling 610 $aconstraint-based modeling 610 $aflux balance 610 $ahost?microbiome 610 $ametabolism 610 $aglobal metabolomics 610 $aLC-MS 610 $aspectra processing 610 $apathway analysis 610 $aenrichment analysis 610 $amass spectrometry 610 $aliquid chromatography 610 $aMS spectral prediction 610 $ametabolite identification 610 $astructure-based chemical classification 610 $arule-based fragmentation 610 $acombinatorial fragmentation 610 $atime series 610 $aPLS 610 $aNPLS 610 $avariable selection 610 $abootstrapped-VIP 610 $adata repository 610 $acomputational metabolomics 610 $areanalysis 610 $alipidomics 610 $adata processing 610 $atriplot 610 $amultivariate risk modeling 610 $aenvironmental factors 610 $adisease risk 610 $achemical classification 610 $ain silico workflows 610 $ametabolome mining 610 $amolecular families 610 $anetworking 610 $asubstructures 610 $amass spectrometry imaging 610 $ametabolomics imaging 610 $abiostatistics 610 $aion selection algorithms 610 $aliquid chromatography high-resolution mass spectrometry 610 $adata-independent acquisition 610 $aall ion fragmentation 610 $atargeted analysis 610 $auntargeted analysis 610 $aR programming 610 $afull-scan MS/MS processing 610 $aR-MetaboList 2 610 $aliquid chromatography?mass spectrometry (LC/MS) 610 $afragmentation (MS/MS) 610 $adata-dependent acquisition (DDA) 610 $asimulator 610 $ain silico 610 $auntargeted metabolomics 610 $aliquid chromatography?mass spectrometry (LC-MS) 610 $aexperimental design 610 $asample preparation 610 $aunivariate and multivariate statistics 610 $ametabolic pathway and network analysis 610 $aLC?MS 610 $ametabolic profiling 610 $acomputational statistical 610 $aunsupervised learning 610 $asupervised learning 615 7$aResearch & information: general 700 $aHanhineva$b Kati$4edt$01328811 702 $aVan der Hooft$b Justin$4edt 702 $aHanhineva$b Kati$4oth 702 $aVan der Hooft$b Justin$4oth 906 $aBOOK 912 $a9910557354403321 996 $aMetabolomics Data Processing and Data Analysis?Current Best Practices$93038980 997 $aUNINA