Related Experiment Video

Updated: Jul 10, 2026

Characterizing Mutational Load and Clonal Composition of Human Blood
07:58

Characterizing Mutational Load and Clonal Composition of Human Blood

Published on: July 11, 2019

Might stochasticity and sampling variation be a possible explanation for variation in clonal population survival

M Witten1

  • 1University of Texas System, Center for High Performance Computing, Balcones Research Center, Austin 78753-4497.

Mechanisms of Ageing and Development
|March 1, 1994
PubMed

More Related Videos

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression12:52

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression

Published on: April 18, 2021

Following the Dynamics of Structural Variants in Experimentally Evolved Populations04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Related Concept Videos

Life Histories01:29

Life Histories

Constrained by limited energy and resources, organisms must compromise between offspring quantity and parental investment. This trade-off is represented by two primary reproductive strategies; K-strategists produce few offspring but provide substantial parental support, whereas r-strategists produce much progeny that receives little care. These strategies are related to an organism’s survival likelihood across its lifespan, which is represented by a survivorship curve. Three general types of...
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...