Meli, Gianfelice
(2019)
On the average generation of a population.
PhD thesis, National University of Ireland Maynooth.
Abstract
Estimating the average generation of a collection of cells is helpful in understanding
complex cellular differentiation processes, identifying carcinogenic
cellular activities, and quantifying the ageing of the immune system. Different
techniques based on both direct observations and indirect inference have
been proposed, with benefits and limitations varying in the two categories.
In this thesis we enhance the mathematical results underpinning one of these
inference methods, firstly proposed by Weber et al. in 2016 [116] and based
on a DNA coded randomised algorithm. Assuming some sort of structure in
the growth of a cell population, with the use of Branching Processes and Renewal
Theory, we establish improved convergence properties of the proposed
estimator to the average generation. Expanding and homeostatic populations
are studied, allowing the method to be used for more complex patterns of
population dynamics that includes the succession of these two phases. Furthermore,
we establish the possibility of using the same method in a two-type
branching process, obtaining a possible criterion to distinguish among some
differentiation models in hemapotoiesis. A quality study of the model allows
also us to establish values of the parameters which improve the performance of
the estimator. Computer simulations, with parametrisations coming from the
immunology field, are along the results with both a validation and exploratory
purpose.
| Item Type: |
Thesis
(PhD)
|
| Keywords: |
average generation; population; |
| Academic Unit: |
Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
| Item ID: |
11007 |
| Depositing User: |
IR eTheses
|
| Date Deposited: |
03 Sep 2019 15:23 |
| URI: |
|
| 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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