MeltDB 2.0 - Advances of the metabolomics software system

Kessler N, Bonte A, Langenkämper G, Niehaus K, Goesmann A, Nattkemper TW (2013)
Bioinformatics 29(19): 2452-2459.

Journal Article | Published | English

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Abstract
Motivation: The research area metabolomics achieved tremendous popularity and development in the last couple of years. Due to its unique interdisciplinarity it requires to combine knowledge from various scientific disciplines. Advances in the high-throughput technology and the consequently growing quality and quantity of data put new demands on applied analytical and computational methods. Exploration of finally generated and analyzed datasets furthermore relies on powerful tools for data mining and visualization. Results: To cover and keep up with these requirements, we have created MeltDB 2.0, a next generation web application adressing storage, sharing, standardization, integration and analysis of metabolomics experiments. New features improve both, efficiency and effectivity of the entire processing pipeline of chromatographic raw data from pre-processing to the derivation of new bioloigcal knowledge. Firstly, the generation of high quality metabolic data sets has been vastly simplified. Secondly, the new statistics tool box allows to investigate these data sets according to a wide spectrum of scientific and explorative questions. Availability: The system is publicly available at https://meltdb.cebitec.unibielefeld. de. A login is required but freely available.
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Kessler N, Bonte A, Langenkämper G, Niehaus K, Goesmann A, Nattkemper TW. MeltDB 2.0 - Advances of the metabolomics software system. Bioinformatics. 2013;29(19):2452-2459.
Kessler, N., Bonte, A., Langenkämper, G., Niehaus, K., Goesmann, A., & Nattkemper, T. W. (2013). MeltDB 2.0 - Advances of the metabolomics software system. Bioinformatics, 29(19), 2452-2459.
Kessler, N., Bonte, A., Langenkämper, G., Niehaus, K., Goesmann, A., and Nattkemper, T. W. (2013). MeltDB 2.0 - Advances of the metabolomics software system. Bioinformatics 29, 2452-2459.
Kessler, N., et al., 2013. MeltDB 2.0 - Advances of the metabolomics software system. Bioinformatics, 29(19), p 2452-2459.
N. Kessler, et al., “MeltDB 2.0 - Advances of the metabolomics software system”, Bioinformatics, vol. 29, 2013, pp. 2452-2459.
Kessler, N., Bonte, A., Langenkämper, G., Niehaus, K., Goesmann, A., Nattkemper, T.W.: MeltDB 2.0 - Advances of the metabolomics software system. Bioinformatics. 29, 2452-2459 (2013).
Kessler, Nikolas, Bonte, Anja, Langenkämper, Georg, Niehaus, Karsten, Goesmann, Alexander, and Nattkemper, Tim Wilhelm. “MeltDB 2.0 - Advances of the metabolomics software system”. Bioinformatics 29.19 (2013): 2452-2459.
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7 Citations in Europe PMC

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Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles.
Hauschild AC, Frisch T, Baumbach JI, Baumbach J., Metabolites 5(2), 2015
PMID: 26065494
MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data.
Kaever A, Landesfeind M, Feussner K, Mosblech A, Heilmann I, Morgenstern B, Feussner I, Meinicke P., Metabolomics 11(3), 2015
PMID: 25972773
Learning to Classify Organic and Conventional Wheat - A Machine Learning Driven Approach Using the MeltDB 2.0 Metabolomics Analysis Platform.
Kessler N, Bonte A, Albaum SP, Mader P, Messmer M, Goesmann A, Niehaus K, Langenkamper G, Nattkemper TW., Front Bioeng Biotechnol 3(), 2015
PMID: 25853128
Method validation strategies involved in non-targeted metabolomics.
Naz S, Vallejo M, Garcia A, Barbas C., J Chromatogr A 1353(), 2014
PMID: 24811151
metaMS: an open-source pipeline for GC-MS-based untargeted metabolomics.
Wehrens R, Weingart G, Mattivi F., J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 966(), 2014
PMID: 24656939

27 References

Data provided by Europe PubMed Central.

Highly sensitive feature detection for high resolution LC/MS.
Tautenhahn R, Bottcher C, Neumann S., BMC Bioinformatics 9(), 2008
PMID: 19040729
MetaboAnalyst: a web server for metabolomic data analysis and interpretation.
Xia J, Psychogios N, Young N, Wishart DS., Nucleic Acids Res. 37(Web Server issue), 2009
PMID: 19429898

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