Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Parallelising a model of bacterial interaction and evolution.

R Gregory1, R Paton, J Saunders

  • 1Department of Computer Science, University of Liverpool, Chadwick Building, Peach Street, Liverpool L69 7ZF, UK. r.gregory@liverpool.ac.uk

Bio Systems
|September 8, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The benefits of plain language summaries in public health publishing.

Perspectives in public health·2025
Same author

Thermodynamic Evidence for Density Wave Order in a Two Dimensional ^{4}He Supersolid.

Physical review letters·2025
Same author

Progression of the faecal microbiome in preweaning dairy calves that develop cryptosporidiosis.

Animal microbiome·2025
Same author

[Clinical analysis of adverse reactions in patients with multidrug-resistant and rifampicin-resistant pulmonary tuberculosis treated with delamanid-containing regimen].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases·2024
Same author

[A survey on the current situation of serum vitamin A and vitamin D levels among children aged 2-<7 years of 20 cities in China].

Zhonghua er ke za zhi = Chinese journal of pediatrics·2024
Same author

[Imaging study on determining the rationality of atlantoaxial fixation angle based on the ratio of line segments between anatomical markers on lateral X-ray films].

Zhonghua yi xue za zhi·2023
Same journal

Ruliological Resilience: Pattern Restoration and Robustness in Wolfram Patterns. A Basis for Regeneration, Not Just in Cone Shells?

Bio Systems·2026
Same journal

The quantum-to-classical transducer: A thermodynamic and quantum mechanical framework for the emergence of bioenergetics.

Bio Systems·2026
Same journal

Forward-backward gene expression binarization for boolean state inference over a known regulatory network.

Bio Systems·2026
Same journal

Partial-label metric ceilings for evaluating gene regulatory networks inferred from single-cell foundation models.

Bio Systems·2026
Same journal

The impedance mismatch theory: A non-equilibrium thermodynamic framework for a shared energetic stress pathway in neurodegeneration.

Bio Systems·2026
Same journal

Immune signal-status misclassification: A theoretical framework for biological status assignment and failed status resolution.

Bio Systems·2026
See all related articles

Simulating bacterial evolution efficiently requires parallel computing and careful problem mapping. This study details a method to model bacterial colonies across multiple scales on fixed resources, optimizing performance.

Area of Science:

  • Computational Biology
  • Microbial Ecology
  • Bioinformatics

Background:

  • Simulating bacterial colonies demands significant computational resources.
  • Efficient performance necessitates parallel computing and optimized problem-to-hardware mapping.

Purpose of the Study:

  • To describe an implementation for modeling bacterial evolution across multiple physical scales.
  • To demonstrate mapping a dynamic, multi-scale problem onto fixed computational resources.

Main Methods:

  • Developed a simulation system composed of individual interacting entities.
  • Modeled individuals at both population and gene product scales.
  • Utilized operating system resource multiplexing and problem partitioning to minimize communication time.

Related Experiment Videos

Main Results:

  • Successfully mapped a dynamic, multi-scale bacterial evolution problem onto fixed computational resources.
  • Achieved efficient simulation performance by maximizing hardware utilization.
  • Avoided constraining the model to excessively specific hardware requirements.

Conclusions:

  • It is feasible to create efficient simulations of complex biological systems like bacterial evolution on general-purpose hardware.
  • Optimized resource utilization and problem partitioning are key to high-performance biological simulations.