- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Annual Issues
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Journal of Biomedicine and Biotechnology
Volume 2012 (2012), Article ID 263910, 7 pages
MarVis-Filter: Ranking, Filtering, Adduct and Isotope Correction of Mass Spectrometry Data
1Department of Bioinformatics, Institute of Microbiology and Genetics, Georg-August-University Göttingen, 37077 Göttingen, Germany
2Department for Plant Biochemistry, Albrecht-von-Haller-Institute for Plant Sciences, Georg-August-University Göttingen, 37077 Göttingen, Germany
3Department of Molecular Microbiology and Genetics, Institute of Microbiology and Genetics, Georg-August-University Göttingen, 37077 Göttingen, Germany
Received 28 July 2011; Revised 18 January 2012; Accepted 18 January 2012
Academic Editor: Brad Upham
Copyright © 2012 Alexander Kaever et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- O. Fiehn, J. Kopka, P. Dörmann, T. Altmann, R. N. Trethewey, and L. Willmitzer, “Metabolite profiling for plant functional genomics,” Nature Biotechnology, vol. 18, no. 11, pp. 1157–1161, 2000.
- J. K. Nicholson, J. C. Lindon, and E. Holmes, “'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data,” Xenobiotica, vol. 29, no. 11, pp. 1181–1189, 1999.
- J. Lisec, N. Schauer, J. Kopka, L. Willmitzer, and A. R. Fernie, “Gas chromatography mass spectrometry-based metabolite profiling in plants,” Nature Protocols, vol. 1, no. 1, pp. 387–396, 2006.
- R. C. H. De Vos, S. Moco, A. Lommen, J. J. B. Keurentjes, R. J. Bino, and R. D. Hall, “Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry,” Nature Protocols, vol. 2, no. 4, pp. 778–791, 2007.
- K. Dettmer, P. A. Aronov, and B. D. Hammock, “Mass spectrometry-based metabolomics,” Mass Spectrometry Reviews, vol. 26, no. 1, pp. 51–78, 2007.
- M. Katajamaa and M. Orešič, “Data processing for mass spectrometry-based metabolomics,” Journal of Chromatography A, vol. 1158, no. 1-2, pp. 318–328, 2007.
- C. A. Smith, E. J. Want, G. O'Maille, R. Abagyan, and G. Siuzdak, “XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification,” Analytical Chemistry, vol. 78, no. 3, pp. 779–787, 2006.
- P. Meinicke, T. Lingner, A. Kaever et al., “Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps,” Algorithms for Molecular Biology, vol. 3, no. 1, article 9, 2008.
- V. Shulaev, D. Cortes, G. Miller, and R. Mittler, “Metabolomics for plant stress response,” Physiologia Plantarum, vol. 132, no. 2, pp. 199–208, 2008.
- L. Tarpley, A. L. Duran, T. H. Kebrom, and L. W. Sumner, “Biomarker metabolites capturing the metabolite variance present in a rice plant developmental period,” BMC Plant Biology, vol. 5, article 8, 2005.
- K. Nahlik, M. Dumkow, Ö Bayram, et al., “The COP9 signalosome mediates transcriptional and metabolic response to hormones, oxidative stress protection and cell wall rearrangement during fungal development,” Molecular Microbiology, vol. 78, no. 4, pp. 964–979, 2010.
- L. Breiman, “Random forests,” Machine Learning, vol. 45, no. 1, pp. 5–32, 2001.
- M. Beckmann, D. P. Enot, D. P. Overy, and J. Draper, “Representation, comparison, and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars,” Journal of Agricultural and Food Chemistry, vol. 55, no. 9, pp. 3444–3451, 2007.
- J. Gibbons and S. Chakraborti, Nonparametric Statistical Inference, CRC Press, 2003.
- A. Koulman, B. A. Tapper, K. Fraser, M. Cao, G. A. Lane, and S. Rasmussen, “High-throughput direct-infusion ion trap mass spectrometry: a new method for metabolomics,” Rapid Communications in Mass Spectrometry, vol. 21, no. 3, pp. 421–428, 2007.
- D. A. MacKenzie, M. Defernez, W. B. Dunn et al., “Relatedness of medically important strains of Saccharomyces cerevisiae as revealed by phylogenetics and metabolomics,” Yeast, vol. 25, no. 7, pp. 501–512, 2008.
- M. Kanehisa and S. Goto, “KEGG: Kyoto encyclopedia of genes and genomes,” Nucleic Acids Research, vol. 28, no. 1, pp. 27–30, 2000.
- P. Zhang, H. Foerster, C. P. Tissier et al., “MetaCyc and AraCyc. Metabolic pathway databases for plant research,” Plant Physiology, vol. 138, no. 1, pp. 27–37, 2005.
- M. Sud, E. Fahy, D. Cotter et al., “LMSD: LIPID MAPS structure database,” Nucleic Acids Research, vol. 35, no. 1, pp. D527–D532, 2007.
- D. S. Wishart, C. Knox, A. C. Guo et al., “HMDB: a knowledgebase for the human metabolome,” Nucleic Acids Research, vol. 37, supplement 1, pp. D603–D610, 2009.
- Y. Wang, J. Xiao, T. O. Suzek, J. Zhang, J. Wang, and S. H. Bryant, “PubChem: a public information system for analyzing bioactivities of small molecules,” Nucleic Acids Research, vol. 37, no. 2, pp. W623–W633, 2009.
- J. Draper, D. P. Enot, D. Parker et al., “Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules',” BMC Bioinformatics, vol. 10, article 227, 2009.
- R. Tautenhahn, C. Böttcher, and S. Neumann, “Annotation of LC/ESI-MS mass signals,” in 1st International Conference on Bioinformatics Research and Development (BIRD '07), vol. 4414 of Lecture Notes in Computer Science, pp. 371–380, Berlin, Germany, March 2007.
- T. Kind and O. Fiehn, “Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry,” BMC Bioinformatics, vol. 8, article 105, 2007.
- R. Gentleman, R. Ihaka, et al., http://www.r-project.org/.
- B. Jones, MATLAB: Statistics Toolbox User's Guide, MathWorks, 1993.
- A. Lommen, “Metalign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing,” Analytical Chemistry, vol. 81, no. 8, pp. 3079–3086, 2009.
- M. Sturm, A. Bertsch, C. Gröpl et al., “OpenMS—an open-source software framework for mass spectrometry,” BMC Bioinformatics, vol. 9, article 163, 2008.
- A. Kaever, T. Lingner, K. Feussner, C. Göbel, I. Feussner, and P. Meinicke, “MarVis: a tool for clustering and visualization of metabolic biomarkers,” BMC Bioinformatics, vol. 10, article 92, 2009.
- S. Holm, “A simple sequentially rejective multiple test procedure,” Scandinavian Journal of Statistics, vol. 6, no. 2, pp. 65–70, 1979.
- Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” Journal of the Royal Statistical Society. Series B, vol. 57, pp. 289–300, 1995.
- B. Von Malek, E. Van Der Graaff, K. Schneitz, and B. Keller, “The Arabidopsis male-sterile mutant dde2-2 is defective in the ALLENE OXIDE SYNTHASE gene encoding one of the key enzymes of the jasmonic acid biosynthesis pathway,” Planta, vol. 216, no. 1, pp. 187–192, 2002.
- C. Göbel and I. Feussner, “Methods for the analysis of oxylipins in plants,” Phytochemistry, vol. 70, no. 13-14, pp. 1485–1503, 2009.
- A. Ibrahim, A. Schütz, J. Galano et al., “The alphabet of galactolipids in Arabidopsis thaliana,” Frontiers in Plant Physiology, vol. 2, article 95, 2011.
- A. Andreou, F. Brodhun, and I. Feussner, “Biosynthesis of oxylipins in non-mammals,” Progress in Lipid Research, vol. 48, no. 3-4, pp. 148–170, 2009.
- G. A. Howe and G. Jander, “Plant immunity to insect herbivores,” Annual Review of Plant Biology, vol. 59, pp. 41–66, 2008.