Exploratory Modeling and Simulation of the Evolutionary Dynamics of Single-Stranded RNA Virus Populations

Yeom, Jae-Seung; Kostova-Vassilevska, Tanya; Barnes, P. D.; Jefferson, David; Oppelstrup, Tomas

doi:10.1109/ipdpsw.2017.139

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…The RNA virus model was inspired by the HIV virus simulated in Reference [19], and we modeled it with the binary string described in Section 2.1. Accordingly, and to simplify the model, many of the biological features of the virus [20][21][22][23][24][25] were not included in the present paper. Figure 2 shows a simple GA adapted to the evolutionary dynamics of a virus.…”

Section: An Evolutionary Algorithm For Viral Cycle Simulationmentioning

confidence: 99%

An Evolutionary Computing Model for the Study of Within-Host Evolution

Gómez-Mompeán

Lahoz-Beltrá

2020

Computation

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Evolution of an individual within another individual is known as within-host dynamics (WHD). The most common modeling technique to study WHD involves ordinary differential equations (ODEs). In the field of biology, models of this kind assume, for example, that both the number of viruses and the number of mouse cells susceptible to being infected change according to their interaction as stated in the ODE model. However, viruses can undergo mutations and, consequently, evolve inside the mouse, whereas the mouse, in turn, displays evolutionary mechanisms through its immune system (e.g., clonal selection), defending against the invading virus. In this work, as the main novelty, we propose an evolutionary WHD model simulating the coexistence of an evolving invader within a host. In addition, instead of using ODEs we developed an alternative methodology consisting of the hybridization of a genetic algorithm with an artificial immune system. Aside from the model, interest in biology, and its potential clinical use, the proposed WHD model may be useful in those cases where the invader exhibits evolutionary changes, for instance, in the design of anti-virus software, intrusion detection algorithms in a corporation’s computer systems, etc. The model successfully simulates two intruder detection paradigms (i.e., humoral detection, danger detection) in which the intruder represents an evolving invader or guest (e.g., virus, computer program,) that infects a host (e.g., mouse, computer memory). The obtained results open up the possibility of simulating environments in which two entities (guest versus host) compete evolutionarily with each other when occupying the same space (e.g., organ cells, computer memory, network).

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Section: An Evolutionary Algorithm For Viral Cycle Simulationmentioning

confidence: 99%

An Evolutionary Computing Model for the Study of Within-Host Evolution

Gómez-Mompeán

Lahoz-Beltrá

2020

Computation

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“…[29]. The frequent mutations in RNA viruses enable them to form highly diverse strains, surviving and reproducing in the environment [30]. In particular, HA has the highest mutation rate (∼5.7 × 10 −3 substitutions per site per year) among all segments [31].…”

Section: Mutation and Reassortment Of Influenza A Virusesmentioning

confidence: 99%

Meta-analysis on the lethality of influenza A viruses using machine learning approaches

Yin¹

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Influenza viruses are persistently threatening public health, causing annual epidemics, and sporadic pandemics. The majority of influenza viruses reside among the avian species due to host range restriction. However, some avian strains do acquire the capability to overcome host species barrier to cause human infections due to mutations and reassortments. These novel influenza strains may cause high

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Exploratory Modeling and Simulation of the Evolutionary Dynamics of Single-Stranded RNA Virus Populations

Cited by 2 publications

References 27 publications

An Evolutionary Computing Model for the Study of Within-Host Evolution

An Evolutionary Computing Model for the Study of Within-Host Evolution

Meta-analysis on the lethality of influenza A viruses using machine learning approaches

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