Publications by authors named "Gemma M Kirwan"

Blood plasma collected from adult fish (black bream, Sparidae) exposed to a dose of 5 mg kg(-1) 17β-estradiol underwent metabonomic profiling using nuclear magnetic resonance (NMR). An extension of the orthogonal 2 projection to latent structure (O2PLS) analysis, tO2PLS, was proposed and utilized to classify changes between the control and experimental metabolic profiles. As a bidirectional modeling tool, O2PLS examines the (variable) commonality between two different data blocks, and extracts the joint correlations as well as the unique variations present within each data block.

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Systems biology methods using large-scale "omics" data sets face unique challenges: integrating and analyzing near limitless data space, while recognizing and removing systematic variation or noise. Herein we propose a complementary multivariate analysis workflow to both integrate "omics" data from disparate sources and analyze the results for specific and unique sample correlations. This workflow combines principal component analysis (PCA), orthogonal projections to latent structures discriminate analysis (OPLS-DA), orthogonal 2 projections to latent structures (O2PLS), and shared and unique structures (SUS) plots.

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Generalized two-dimensional (Gen2D) correlation analysis and hybrid correlation analysis have been applied to a series of dynamic (31)P nuclear magnetic resonance (NMR) spectra to monitor the in vivo metabolic changes of the plant pathogen Phytophthora palmivora in the presence and absence of phosphonate over an 18-h period. Results indicate that phosphonate exposure causes cleavage in organism polyphosphate chains as well as an increase in total sugar phosphates. In the presence of phosphonate, the NMR resonances attributed to terminal polyphosphate phosphorus reduced at a lower rate than those of middle polyphosphate phosphorus, indicating a change in average chain length and suggesting cleavage in the middle of the chain as well as at the ends.

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Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY).

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A wine fermentation has been monitored on a daily basis by (1)H NMR spectroscopy. Following data pre-processing that includes synthesis of the spectra to ensure all peaks are of constant half-width, the series of spectra were examined using generalised two-dimensional correlation techniques. Synchronous and asynchronous data maps have been generated and employed to interpret the changes in the fermentation process as a function of time.

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