Shauna O'Donovan successfully defends thesis
The human body is a highly complex system operating over several spatiotemporal scales. Advances in measurement techniques, particularly the advent of high through-put omics technologies, in recent decades has greatly improved our understanding of the human system, and how the biological entities in each sub-network from cells, to tissues and organs interact to give rise to systemic responses.
However, how to effectively process, integrate, and analyse this often very high dimensional data presents poses one of the biggest challenges to biological researches today. In this thesis, 'Modelling the Dynamics in Time Series of Metabolomics and Transcriptomics Data' we have focused on a range of computational approaches that allow multivariate time series of biological data to be integrated, analysed, and interpreted.
While the challenges of analysing time series data are common to several biological disciplines in this thesis we have elected to focus on two specific cases; the minimally invasive assessment of metabolic health in the obese system and alternatives to animal testing in toxicological screening. Nevertheless, the approaches used in this thesis can be generalised to several biological disciplines. Moreover, all chapters of this thesis re-use existing data, generating novel insights from previously published data
Read whole thesis here
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