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Patrick Giavalisco

Researcher at Max Planck Society

Publications -  144
Citations -  9476

Patrick Giavalisco is an academic researcher from Max Planck Society. The author has contributed to research in topics: Metabolomics & Gene. The author has an hindex of 46, co-authored 131 publications receiving 7412 citations.

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Intra- and interspecific variation in primate gene expression patterns

TL;DR: Three mouse species that are approximately as related to each other as are humans, chimpanzees, and orangutans are studied, and species-specific gene expression patterns indicating that changes in protein and gene expression have been particularly pronounced in the human brain are identified.
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Elemental formula annotation of polar and lipophilic metabolites using 13C, 15N and 34S isotope labelling, in combination with high-resolution mass spectrometry

TL;DR: A comprehensive multi-isotope labelling-based strategy using fully labelled plant tissues, in combination with a fractionated metabolite extraction protocol, which can be applied in either an automated database-dependent or a database-independent analysis of the plant polar metabolome and lipidome.
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The sucrose–trehalose 6-phosphate (Tre6P) nexus: specificity and mechanisms of sucrose signalling by Tre6P

TL;DR: Trehalose-6-phosphate is a signal of sucrose status in plants and forms part of a homeostatic mechanism that maintains sucrose levels within a range that is appropriate for the cell type and stage of development.
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Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices

TL;DR: In this article, the authors present guidelines covering sample preparation, replication and randomization, quantification, recovery and recombination, ion suppression and peak misidentification, as a means to enable high-quality reporting of liquid chromatography and gas chromatography-mass spectrometry-derived data.
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Comprehensive Dissection of Spatiotemporal Metabolic Shifts in Primary, Secondary, and Lipid Metabolism during Developmental Senescence in Arabidopsis

TL;DR: The metabolome data and the approach provided here can serve as a blueprint for the analysis of traits and conditions linking crop yield and senescence as well as provide clues to source-sink relations.