Ridout, Martin S. (2008) Computational methods for yeast prion curing curves. Mathematical Biosciences, 215 (2). pp. 152-157. ISSN 0025-5564. (doi:10.1016/j.mbs.2008.07.008) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:15620)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1016/j.mbs.2008.07.008 |
Abstract
If the chemical guanidine hydrochloride is added to a dividing culture of yeast cells in which some of the protein Sup35p is in its prion form. the proportion of cells that carry replicating units of the prion, termed propagons, decreases gradually over time. Stochastic models to describe this process of 'curing' have been developed in earlier work. The present paper investigates the use of numerical methods of Laplace transform inversion to calculate curing curves and contrasts this with an alternative, more direct, approach that involves numerical integration. Transform inversion is found to provide a much more efficient computational approach that allows different models to be investigated with minimal programming effort. The method is used to investigate the robustness of the curing curve to changes in the assumed distribution of cell generation times. Matlab code is available for carrying out the calculations.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.mbs.2008.07.008 |
Uncontrolled keywords: | Age-dependent branching process; Fast Fourier transform; Laplace transform numerical transform inversion; Renewal process; Saccharomyces cerevisiae |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Maureen Cook |
Date Deposited: | 23 Feb 2010 13:00 UTC |
Last Modified: | 05 Nov 2024 09:50 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/15620 (The current URI for this page, for reference purposes) |
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