A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory-Reference-Cited by-同舟云学术

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A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory

Published:2018-07-06 Issue: Volume:9 Page:
ISSN:1664-302X
Container-title:Frontiers in Microbiology
language:
Short-container-title:Front. Microbiol.

Author:

Carruthers Jonathan,López-García Martín,Gillard Joseph J.,Laws Thomas R.,Lythe Grant,Molina-París Carmen

Funder

Medical Research Council

Engineering and Physical Sciences Research Council

Seventh Framework Programme

Defence Science and Technology Laboratory

Publisher

Frontiers Media SA

Subject

Microbiology (medical),Microbiology

Reference33 articles.

1. Agent-based modeling of host–pathogen systems: the successes and challenges;Bauer;Inform. Sci.,2009

2. Complement c3 as a prompt for human macrophage death during infection with francisella tularensis strain schu s4;Brock;Infect. Immun.,2017

3. Efficient step size selection for the tau-leaping simulation method;Cao;J. Chem. Phys.,2006

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1. Quantifying in vitro B. anthracis growth and PA production and decay: a mathematical modelling approach;npj Systems Biology and Applications;2024-03-29

2. Using mixture density networks to emulate a stochastic within-host model of Francisella tularensis infection;PLOS Computational Biology;2023-12-20

3. Using mixture density networks to emulate a stochastic within-host model ofFrancisella tularensisinfection;2023-06-16

4. A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity;Frontiers in Immunology;2021-08-23

5. Efficacy of antibiotic medication strategy following a bioterrorist attack involving Francisella tularensis;Journal of the Operational Research Society;2021-08-13

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