Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data

Henning P, Kuich JL, Hoffmann N, Stefan K (2015)
Frontiers in Bioengineering and Biotechnology 2(84): 84.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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DOI
Autor*in
Henning, Peter; Kuich, Julius Lloyd; Hoffmann, NilsUniBi ; Stefan, Kempa
Einrichtung
Centrum für Biotechnologie > Arbeitsgruppe J. Stoye
Technische Fakultät > AG Genominformatik
Erscheinungsjahr
2015
Zeitschriftentitel
Frontiers in Bioengineering and Biotechnology
Band
2
Ausgabe
84
Seite(n)
84
ISSN
2296-4185
Page URI
https://pub.uni-bielefeld.de/record/2715682

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Henning P, Kuich JL, Hoffmann N, Stefan K. Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data. Frontiers in Bioengineering and Biotechnology. 2015;2(84):84.
Henning, P., Kuich, J. L., Hoffmann, N., & Stefan, K. (2015). Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data. Frontiers in Bioengineering and Biotechnology, 2(84), 84. doi:10.3389/fbioe.2014.00084
Henning, Peter, Kuich, Julius Lloyd, Hoffmann, Nils, and Stefan, Kempa. 2015. “Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data”. Frontiers in Bioengineering and Biotechnology 2 (84): 84.
Henning, P., Kuich, J. L., Hoffmann, N., and Stefan, K. (2015). Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data. Frontiers in Bioengineering and Biotechnology 2, 84.
Henning, P., et al., 2015. Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data. Frontiers in Bioengineering and Biotechnology, 2(84), p 84.
P. Henning, et al., “Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data”, Frontiers in Bioengineering and Biotechnology, vol. 2, 2015, pp. 84.
Henning, P., Kuich, J.L., Hoffmann, N., Stefan, K.: Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data. Frontiers in Bioengineering and Biotechnology. 2, 84 (2015).
Henning, Peter, Kuich, Julius Lloyd, Hoffmann, Nils, and Stefan, Kempa. “Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data”. Frontiers in Bioengineering and Biotechnology 2.84 (2015): 84.

6 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

The Chemistry of Plant-Microbe Interactions in the Rhizosphere and the Potential for Metabolomics to Reveal Signaling Related to Defense Priming and Induced Systemic Resistance.
Mhlongo MI, Piater LA, Madala NE, Labuschagne N, Dubery IA., Front Plant Sci 9(), 2018
PMID: 29479360
Alterations of mTOR signaling impact metabolic stress resistance in colorectal carcinomas with BRAF and KRAS mutations.
Fritsche-Guenther R, Zasada C, Mastrobuoni G, Royla N, Rainer R, Roßner F, Pietzke M, Klipp E, Sers C, Kempa S., Sci Rep 8(1), 2018
PMID: 29907857
Fructose-driven glycolysis supports anoxia resistance in the naked mole-rat.
Park TJ, Reznick J, Peterson BL, Blass G, Omerbašić D, Bennett NC, Kuich PHJL, Zasada C, Browe BM, Hamann W, Applegate DT, Radke MH, Kosten T, Lutermann H, Gavaghan V, Eigenbrod O, Bégay V, Amoroso VG, Govind V, Minshall RD, Smith ESJ, Larson J, Gotthardt M, Kempa S, Lewin GR., Science 356(6335), 2017
PMID: 28428423
The B-cell receptor controls fitness of MYC-driven lymphoma cells via GSK3β inhibition.
Varano G, Raffel S, Sormani M, Zanardi F, Lonardi S, Zasada C, Perucho L, Petrocelli V, Haake A, Lee AK, Bugatti M, Paul U, Van Anken E, Pasqualucci L, Rabadan R, Siebert R, Kempa S, Ponzoni M, Facchetti F, Rajewsky K, Casola S., Nature 546(7657), 2017
PMID: 28562582
Salt-responsive gut commensal modulates TH17 axis and disease.
Wilck N, Matus MG, Kearney SM, Olesen SW, Forslund K, Bartolomaeus H, Haase S, Mähler A, Balogh A, Markó L, Vvedenskaya O, Kleiner FH, Tsvetkov D, Klug L, Costea PI, Sunagawa S, Maier L, Rakova N, Schatz V, Neubert P, Frätzer C, Krannich A, Gollasch M, Grohme DA, Côrte-Real BF, Gerlach RG, Basic M, Typas A, Wu C, Titze JM, Jantsch J, Boschmann M, Dechend R, Kleinewietfeld M, Kempa S, Bork P, Linker RA, Alm EJ, Müller DN., Nature 551(7682), 2017
PMID: 29143823
Updates in metabolomics tools and resources: 2014-2015.
Misra BB, van der Hooft JJ., Electrophoresis 37(1), 2016
PMID: 26464019

20 References

Daten bereitgestellt von Europe PubMed Central.

Controlling the false discovery rate: a practical and powerful approach to multiple testing
Benjamini Y., Hochberg Y.., 1995
Advances in mass spectrometry for lipidomics.
Blanksby SJ, Mitchell TW., Annu Rev Anal Chem (Palo Alto Calif) 3(), 2010
PMID: 20636050
Comparative evaluation of preprocessing freeware on chromatography/mass spectrometry data for signature discovery.
Coble JB, Fraga CG., J Chromatogr A 1358(), 2014
PMID: 25063004
Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy.
Dunn WB, Broadhurst DI, Atherton HJ, Goodacre R, Griffin JL., Chem Soc Rev 40(1), 2010
PMID: 20717559
Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets.
Hoffmann N, Keck M, Neuweger H, Wilhelm M, Hogy P, Niehaus K, Stoye J., BMC Bioinformatics 13(), 2012
PMID: 22920415
BiPACE 2D--graph-based multiple alignment for comprehensive 2D gas chromatography-mass spectrometry.
Hoffmann N, Wilhelm M, Doebbe A, Niehaus K, Stoye J., Bioinformatics 30(7), 2013
PMID: 24363380
High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses.
Jonsson P, Johansson AI, Gullberg J, Trygg J, A J, Grung B, Marklund S, Sjostrom M, Antti H, Moritz T., Anal. Chem. 77(17), 2005
PMID: 16131076
Gas-chromatographische Charakterisierung organischer Verbindungen. Teil 1: Retentionsindices aliphatischer Halogenide, Alkohole, Aldehyde und Ketone
Kovats E.., 1958
Gas chromatography mass spectrometry-based metabolite profiling in plants.
Lisec J, Schauer N, Kopka J, Willmitzer L, Fernie AR., Nat Protoc 1(1), 2006
PMID: 17406261
MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing.
Lommen A., Anal. Chem. 81(8), 2009
PMID: 19301908
TagFinder for the quantitative analysis of gas chromatography--mass spectrometry (GC-MS)-based metabolite profiling experiments.
Luedemann A, Strassburg K, Erban A, Kopka J., Bioinformatics 24(5), 2008
PMID: 18204057
mzML--a community standard for mass spectrometry data.
Martens L, Chambers M, Sturm M, Kessner D, Levander F, Shofstahl J, Tang WH, Rompp A, Neumann S, Pizarro AD, Montecchi-Palazzi L, Tasman N, Coleman M, Reisinger F, Souda P, Hermjakob H, Binz PA, Deutsch EW., Mol. Cell Proteomics 10(1), 2010
PMID: 20716697
Proteome dynamics and early salt stress response of the photosynthetic organism Chlamydomonas reinhardtii.
Mastrobuoni G, Irgang S, Pietzke M, Assmus HE, Wenzel M, Schulze WX, Kempa S., BMC Genomics 13(), 2012
PMID: 22651860
Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.
Pietzke M, Zasada C, Mudrich S, Kempa S., Cancer Metab 2(), 2014
PMID: 25035808
MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data.
Pluskal T, Castillo S, Villar-Briones A, Oresic M., BMC Bioinformatics 11(), 2010
PMID: 20650010
XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.
Smith CA, Want EJ, O'Maille G, Abagyan R, Siuzdak G., Anal. Chem. 78(3), 2006
PMID: 16448051
Retention index thresholds for compound matching in GC-MS metabolite profiling.
Strehmel N, Hummel J, Erban A, Strassburg K, Kopka J., J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 871(2), 2008
PMID: 18501684
Plant metabolomics: large-scale phytochemistry in the functional genomics era.
Sumner LW, Mendes P, Dixon RA., Phytochemistry 62(6), 2003
PMID: 12590110
A GENERALIZATION OF THE RETENTION INDEX SYSTEM INCLUDING LINEAR TEMPERATURE PROGRAMMED GAS-LIQUID PARTITION CHROMATOGRAPHY.
VANDENDOOL H, KRATZ PD., J. Chromatogr. 11(), 1963
PMID: 14062605
Modern analytical techniques in metabolomics analysis.
Zhang A, Sun H, Wang P, Han Y, Wang X., Analyst 137(2), 2011
PMID: 22102985
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