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

Somatic mutations and ageing in silico.

Thomas B L Kirkwood1, Carole J Proctor

  • 1Department of Gerontology, University of Newcastle, Institute for Ageing and Health, Newcastle General Hospital, NE4 6BE, Newcastle upon Tyne, UK. tom.kirkwood@ncl.ac.uk <tom.kirkwood@ncl.ac.uk>

Mechanisms of Ageing and Development
|March 6, 2003
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

Inferring accumulation times of mitochondrial DNA deletion mutants from cross-sectional single-cell data: methodological framework and validation.

npj aging·2026
Same author

Author Correction: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing.

Scientific reports·2023
Same author

Immunosenescence profiles of lymphocyte compartments and multiple long-term conditions (multimorbidity) in very old adults: The Newcastle 85+ Study.

Mechanisms of ageing and development·2022
Same author

Senolytics and the compression of late-life mortality.

Experimental gerontology·2021
Same author

Aging as a consequence of selection to reduce the environmental risk of dying.

Proceedings of the National Academy of Sciences of the United States of America·2021
Same author

Publisher Correction: A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Nature communications·2021
Same journal

Human sex-specific hormone effects on cerebrovascular health in males and females.

Mechanisms of ageing and development·2026
Same journal

HTZ-1/H2A.Z expression sustains transcriptional programs that regulate Caenorhabditis elegans lifespan.

Mechanisms of ageing and development·2026
Same journal

PCSK9 promotes aging-related cardiac calcification by inducing osteogenic differentiation of cardiac fibroblasts.

Mechanisms of ageing and development·2026
Same journal

Distinct post-infectious TLR2 immune remodeling in COVID-19-recovered centenarians.

Mechanisms of ageing and development·2026
Same journal

Senescence-associated tertiary lymphoid structures in Sjögren's disease model nishiura mice.

Mechanisms of ageing and development·2026
Same journal

Aging-driven reprogramming of CD34⁺ hematopoietic stem cells in leukemogenesis: Mechanisms and therapeutic implications.

Mechanisms of ageing and development·2026
See all related articles

Somatic mutations accumulate with age, but their causal role in aging remains unclear. In silico models explore how these mutations impact cell populations, aiding the understanding of aging

Area of Science:

  • Gerontology and Molecular Biology
  • Computational Biology and Bioinformatics

Background:

  • Accumulation of somatic mutations is observed in aging cells and organisms.
  • The causative role of these mutations in the aging process is not fully understood.
  • Cellular-level selection may hinder mutation accumulation in dividing cells, posing a challenge to the somatic mutation theory of aging.

Purpose of the Study:

  • To develop in silico models for exploring the role of somatic mutations in aging.
  • To investigate the rate and dynamic profile of somatic mutation accumulation.
  • To address the complexity of functional genomics in aging.

Main Methods:

  • Development of in silico computational models.
  • Mathematical modeling of mutation dynamics in cell populations.

Related Experiment Videos

  • Simulation of somatic mutation effects in dividing cells, such as human fibroblasts.

    • Main Results:

    • The study presents novel in silico models for aging research.
    • These models facilitate the exploration of somatic mutation impacts on cell populations.
    • The models are designed to address challenges posed by cellular selection in dividing cells.

    Conclusions:

    • In silico models are valuable tools for unraveling the functional genomics of aging.
    • Further development of predictive mathematical and computer models is crucial.
    • Understanding somatic mutation dynamics is key to understanding the aging process.