Computational approaches that aid annotation in metabolomics

de Souza, L. P.; Naake, T.; Fernie, A. R.

doi:10.1016/j.tplants.2022.06.010

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Computational approaches that aid annotation in metabolomics

de Souza, L. P., Naake, T., & Fernie, A. R. (2022). Computational approaches that aid annotation in metabolomics. Trends in Plant Science, 27(10), 1077-1078. doi:10.1016/j.tplants.2022.06.010.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000A-D2B3-E Version Permalink: https://hdl.handle.net/21.11116/0000-000B-156E-3

Genre: Journal Article

Alternative Title : Trends in Plant Science

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Creators:
de Souza, L. P.¹, Author
Naake, T.², Author
Fernie, A. R.¹, Author

Affiliations:
1Central Metabolism, Department Gutjahr, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_3396323
2Central Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753339

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Language(s): eng - English

Dates: Published Online: 2022-07-22Date issued: 2022-10

Publication Status: Issued

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Identifiers: DOI: 10.1016/j.tplants.2022.06.010

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Title: Trends in Plant Science

Other : Trends Plant Sci.

Source Genre: Journal

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Publ. Info: Kidlington, Oxford : Elsevier Current Trends

Pages: - Volume / Issue: 27 (10) Sequence Number: - Start / End Page: 1077 - 1078 Identifier: ISSN: 1360-1385
CoNE: https://pure.mpg.de/cone/journals/resource/954925619141