Related Experiment Video

Updated: Aug 10, 2026

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model
08:46

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model

Published on: September 29, 2011

A mathematical model of the physiological dynamics of aging and correlated mortality selection: II. Application to

K G Manton, M A Woodbury

    Journal of Gerontology
    |July 1, 1983
    PubMed

    More Related Videos

    Measurement of Lifespan in Drosophila melanogaster10:00

    Measurement of Lifespan in Drosophila melanogaster

    Published on: January 7, 2013

    High-Throughput Behavioral Aging and Lifespan Assays Using the Lifespan Machine08:53

    High-Throughput Behavioral Aging and Lifespan Assays Using the Lifespan Machine

    Published on: January 26, 2024

    Related Concept Videos

    Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

    Mechanistic Models: Compartment Models in Individual and Population Analysis

    Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
    Pharmacodynamics in Geriatric Patients: Effects of Age01:27

    Pharmacodynamics in Geriatric Patients: Effects of Age

    Age-related pharmacokinetic changes are extensively documented, but understanding age-related pharmacodynamic alterations is relatively limited. This knowledge gap can be partly attributed to the complexity of developing appropriate measures of drug responses compared to bioanalytical methods for determining drug concentrations.Most information regarding age-related differences in human pharmacodynamics originates from cross-sectional studies. However, these studies assume that observed mean...
    Applications of Life Tables01:22

    Applications of Life Tables

    Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
    Aging01:26

    Aging

    Aging is a complex biological phenomenon influenced by various processes that affect cellular and systemic functions. Several prominent theories attempt to explain its mechanisms, highlighting cellular limitations, oxidative damage, and hormonal changes as central factors in aging.
    Cellular Clock Theory
    The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
    Exponential Equations for Modeling Growth01:26

    Exponential Equations for Modeling Growth

    Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is the relative...
    Modeling with Differential Equations01:25

    Modeling with Differential Equations

    Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...