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1 to 6 of 6 Results
Aug 21, 2018 - PFEM Dataverse
Cédric Delporte; Florence Souard, 2018, "W4M00007_Coffea-leaves", https://doi.org/10.15454/1.4985472277740251E12, Portail Data Inra, V2
Abstract:Study: Characterization of the coffee leaves metabolome composition in 9 species of Coffea (Rubiaceae) collected at 5 dates in 2016 (January – March - July- September – December) after aqueous extraction. A total of 169 samples (including 147 individual samples, 8 blanks...
Aug 20, 2018 - PFEM Dataverse
Marie Tremblay-Franco, 2018, "W4M00006_BPA-MMusculus", https://doi.org/10.15454/1.4821558812795176E12, Portail Data Inra, V2
Abstract:Study: Metabolic shifts induced in vivo after perinatal exposure to low doses of BPA in CD-1 mice were assessed. In this study conducted by the ToxAlim-MeX team and the Tufts University school of medicine (Boston, MA, USA) in collaboration with the AXIOM-MetaToul-MetaboH...
Aug 20, 2018 - PFEM Dataverse
Yann Guitton; Sophie Goulitquer, 2018, "W4M00004_GCMS-Algae", https://doi.org/10.15454/1.4811272313071519E12, Portail Data Inra, V2
Abstract:Study: Characterization of the physiological variations of the metabolome in algae exposed to 3 different abiotic stress (salt concentration). Dataset: The dataset contains 12 mzXML files created from Agilent RAW GC-MS file. 4 replicats per conditions: i) Condition 01: F...
Aug 20, 2018 - PFEM Dataverse
Etienne Thévenot; Philippe Rinaudo, 2018, "W4M00003_Diaplasma", https://doi.org/10.15454/1.4811165052113186E12, Portail Data Inra, V2
Abstract:Study: Identification of metabolomics signatures for patient stratification between type 1 versus type 2 diabetes mellitus. Dataset: plasma samples from 69 diabetic patients were analyzed by reversed phase (C18) ultra-high performance liquid chromatography (UPLC) coupled...
Aug 20, 2018 - PFEM Dataverse
Etienne Thévenot, 2018, "W4M00002_Sacurine-comprehensive", https://doi.org/10.15454/1.481114233733302E12, Portail Data Inra, V2
Abstract:Study: Characterization of the physiological variations of the metabolome in biofluids is critical to understand human physiology and to avoid confounding effects in cohort studies aiming at biomarker discovery. In this study conducted by the MetaboHUB French Infrastruct...
Aug 20, 2018 - PFEM Dataverse
Etienne Thévenot, 2018, "W4M00001_Sacurine-statistics", https://doi.org/10.15454/1.4811121736910142E12, Portail Data Inra, V2
Abstract:Study: Characterization of the physiological variations of the metabolome in biofluids is critical to understand human physiology and to avoid confounding effects in cohort studies aiming at biomarker discovery. Dataset: In this study conducted by the MetaboHUB French In...
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