Prevedello, Giulio (2018) A mathematical framework for clonal data analysis. PhD thesis, National University of Ireland Maynooth.
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Abstract
This dissertation reports on the development of the mathematical and statistical framework
that was necessary for the analysis of data from a novel single-cell assay designed
to address questions in fundamental biology. Many biological systems function by generating
new cells from activated ancestors through cellular division. To investigate such
systems, a high throughput experimental protocol was recently developed that marks
initial cells so that their cellular offspring, the number of rounds of division from their
ancestor, and their phenotype can be determined. The clonal data that result from this
technique, however, are characterised by familial associations that impede their analysis
using classical quantitative tools, necessitating the development of a new mathematical
framework where suitable statistics are formulated that take these complex dependencies
into account. The design, development and implementation of that framework, as
well as inferences made from its use, are the subject of the present thesis.
Item Type: | Thesis (PhD) |
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Keywords: | mathematical framework; clonal data; analysis; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 10652 |
Depositing User: | IR eTheses |
Date Deposited: | 27 Mar 2019 09:46 |
URI: | https://mu.eprints-hosting.org/id/eprint/10652 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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