Simple Data-Reduction Method for High-Resolution LC–MS Data in Metabolomics

• Fiehn O . Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp. Funct. Genomics. 2(3), 155–168 (2001).
   PubMed Web of Science ®Google Scholar
• Han J , DanellR, PatelJet al. Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry. Metabolomics4(2), 128–140 (2008).
   PubMed Web of Science ®Google Scholar
• Atherton HJ , BaileyNJ, ZhangWet al. A combined 1H-NMR spectroscopy- and mass spectrometry-based metabolomic study of the PPAR-α null mutant mouse defines profound systemic changes in metabolism linked to the metabolic syndrome. Physiol. Genomics27(2), 178–186 (2006).
   PubMed Web of Science ®Google Scholar
• Dunn WB , BroadhurstD, BrownMet al. Metabolic profiling of serum using ultra performance liquid chromatography and the LTQ-Orbitrap mass spectrometry system. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 871(2), 288–298 (2008).
   PubMed Web of Science ®Google Scholar
• van der Werf MJ , OverkampKM, MuilwijkB, CoulierL, HankemeierT. Microbial metabolomics: toward a platform with full metabolome coverage. Anal. Biochem. 370(1), 17–25 (2007).
   PubMed Web of Science ®Google Scholar
• Scalbert A , BrennanL, FiehnOet al. Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics DOI: 10.1007/s11306-009-0168-0. (2009) (Epub ahead of print).
   PubMed Web of Science ®Google Scholar
• Tautenhahn R , BöttcherC, NeumannS. Annotation of LC/ESI-MS mass signals. In:Bioinformatics Research and Development. Hochreiter S, Wagner R (Ed.). Springer-Verlag, Heidelberg, Germany, 371–380 (2007).
   Google Scholar
• Tikunov Y , LommenA, de Vos CRet al. A novel approach for nontargeted data analysis for metabolomics. Large-scale profiling of tomato fruit volatiles. Plant Physiol. 139(3), 1125–1137 (2005).
   PubMed Web of Science ®Google Scholar
• Luedemann A , StrassburgK, ErbanA, KopkaJ. TagFinder for the quantitative analysis of gas chromatography–mass spectrometry (GC–MS)-based metabolite profiling experiments. Bioinformatics24(5), 732–737 (2008).
   PubMed Web of Science ®Google Scholar
• Fu J , JansenRC. Optimal design and analysis of genetic studies on gene expression. Genetics172(3), 1993–1999 (2006).
   PubMed Web of Science ®Google Scholar
• Fu J , KeurentjesJJB, BouwmeesterHet al. System-wide molecular evidence for phenotypic buffering in Arabidopsis. Nat. Genet. 41(2), 166–167 (2009).
   PubMed Web of Science ®Google Scholar
• Gieger C , GeistlingerL, AltmaierEet al. Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum. PLoS Genet. 4(11), e1000282 (2008).
   PubMed Web of Science ®Google Scholar
• Kim JK , BambaT, HaradaK, FukusakiE, KobayashiA. Time-course metabolic profiling in Arabidopsis thaliana cell cultures after salt stress treatment. J. Exp. Bot. 58(3), 415–424 (2006).
   PubMed Web of Science ®Google Scholar
• Smith CA , WantEJ, O’MailleG, AbagyanR, SiuzdakG. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78(3), 779–787 (2006).
   PubMed Web of Science ®Google Scholar
• Scheltema RA , KamlehA, WildridgeDet al. Increasing the mass accuracy of high-resolution LC-MS data using background ions: a case study on the LTQ-Orbitrap. Proteomics8(22), 4647–4656 (2008).
   PubMed Web of Science ®Google Scholar
• Christin C , SmildeAK, HoefslootHCJet al. Optimized time alignment algorithm for LC-MS data: correlation optimized warping using component detection algorithm-selected mass chromatograms. Anal. Chem. 80(18), 7012–7021 (2008).
   PubMed Web of Science ®Google Scholar
• Keller BO , SuiJ, YoungAB, WhittalRM. Interferences and contaminants encountered in modern mass spectrometry. Anal. Chim. Acta627(1), 71–81 (2008).
   PubMed Web of Science ®Google Scholar
• Shah V , MidhaK, FindlayJet al. Bioanalytical method validation – a revisit with a decade of progress. Pharm. Res. 17(12), 1551–1557 (2000).
   PubMedGoogle Scholar
• Doyle M , MacRaeJ, De Souza Det al. LeishCyc: a biochemical pathways database for Leishmania major. BMC Systems Biol. 3(1), 57 (2009).
   PubMedGoogle Scholar
• Kanehisa M , GotoS, KawashimaS, NakayaA. The KEGG databases at GenomeNet. Nucleic Acids Res. 30(1), 42–46 (2002).
   PubMed Web of Science ®Google Scholar
• Wishart DS , TzurD, KnoxCet al. HMDB: the human metabolome database. Nucleic Acids Res. 35(Suppl.), D521–D526 (2007).
   PubMedGoogle Scholar
• Fahy E , SudM, CotterD, SubramaniamS. LIPID MAPS online tools for lipid research. Nucleic Acids Res. 35(Suppl.), W606–W612 (2007).
   PubMedGoogle Scholar
• Kind T , FiehnO. Seven golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinformatics8(1), 105 (2007).
   PubMedGoogle Scholar
• Breitling R , RitchieS, GoodenoweD, StewartML, BarrettMP. Ab initio prediction of metabolic networks using Fourier transform mass spectrometry data. Metabolomics2(3), 155–164 (2006).
   PubMed Web of Science ®Google Scholar
• Pan Z , RafteryD. Comparing and combining NMR spectroscopy and mass spectrometry in metabolomics. Anal. Bioanal. Chem. 387(2), 525–527 (2007).
   PubMed Web of Science ®Google Scholar
• Rogers S , ScheltemaRA, GirolamiM, BreitlingR. Probabilistic assignment of formulas to mass peaks in metabolomics experiments. Bioinformatics25(4), 512–518 (2009).
   PubMed Web of Science ®Google Scholar

Website

• MS adduct calculator provided by the Fiehn lab. http://fiehnlab.ucdavis.edu/staff/kind/Metabolomics/MS-Adduct-Calculator/
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