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Title: Deep metabolome annotation of the freshwater model species, Daphnia magna
Author: Jones, Martin Robert
ISNI:       0000 0004 7432 290X
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2017
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In the 21st century - the era of big data science - chemical risk assessment procedures remain woefully dependent upon a suite of basic toxicological assays that offer little, if any, biochemical information pertaining to the underlying mechanism of toxicity. Metabolomics, defined as the holistic study of all naturally occurring, low molecular weight metabolites present within a biological system, holds huge potential as a tool to fill this knowledge gap, and thereby, to revolutionise the chemical risk assessment process through provision of rich molecular information . Owing to on-going challenges in the area of metabolite identification, however, which ultimately serves to impede derivation of biological knowledge from metabolomics data sets, the full potential of the metabolomics platform has yet to be realised in the context of (eco-)toxicological research. In this thesis, I present the experiments undertaken in establishing a bespoke bioanalytical workflow specifically designed and optimised to resolve this bottleneck. Ultimately, I demonstrate application of select components of this workflow in the characterisation of the metabolome of D. magna, a model organism for eco-toxicological research.
Supervisor: Not available Sponsor: Natural Environmental Research Council (NERC) ; Thermo Fisher Scientific
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Q Science (General)