Alamino, R.C. (2020). An Agent-Based Lattice Model for the Emergence of Anti-Microbial Resistance. Journal of Theoretical Biology, 486 ,
Abstract
This work introduces a new probabilistic agent-based lattice model for studying the emergence of anti-microbial resistance (AMR) and proposes a new proxy to measure it: the average death probability of the population under the action of the AMD. Both analytical studies and computer simulations of the microscopic behaviour of a bacterial culture interacting with anti-microbial drugs on a discrete lattice are carried out by focusing on the dynamics of this quantity. A unique genotype-phenotype map and classes of AMDs follow as emergent properties and their effects on the possible reversal of resistance are analysed. We also discuss briefly the possibility of using machine learning techniques to learn the model parameters.
Publication DOI: | https://doi.org/10.1016/j.jtbi.2019.110080 |
---|---|
Divisions: | College of Engineering & Physical Sciences > Systems analytics research institute (SARI) College of Engineering & Physical Sciences |
Additional Information: | © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Uncontrolled Keywords: | Perceptron,Probabilistic model,Resistance reversal,Single-drug protocol,Statistics and Probability,Modelling and Simulation,General Biochemistry,Genetics and Molecular Biology,General Immunology and Microbiology,General Agricultural and Biological Sciences,Applied Mathematics |
Publication ISSN: | 1095-8541 |
Last Modified: | 21 Nov 2024 17:22 |
Date Deposited: | 13 Nov 2019 10:34 |
Full Text Link: | |
Related URLs: |
https://linking ... 022519319304497
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2020-02-07 |
Published Online Date: | 2019-11-12 |
Accepted Date: | 2019-11-11 |
Authors: |
Alamino, R.C.
(
0000-0001-8224-2801)
|
Download
Version: Accepted Version
License: Creative Commons Attribution Non-commercial No Derivatives
| Preview