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Related Concept Videos

Variability: Analysis01:11

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
Reliability and Validity01:29

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
Stability01:28

Stability

The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
Coefficient of Variation01:10

Coefficient of Variation

The coefficient of variation measures the dispersion of the data points or distribution around the mean. Using the coefficient of variation, we can compare two data series with drastically different means or different units of measurement. The coefficient of variation for a sample and a population is expressed as a percentage of the ratio of standard deviation to the mean.
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
Uncertainty: Overview00:59

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
Continuity of a Function01:23

Continuity of a Function

A function is continuous at a point a if three conditions are met: the function is defined at a, the limit of the function as x approaches a exists, and this limit equals the function’s value. Mathematically, this is written asThis definition ensures the graph of the function does not exhibit any breaks, holes, or jumps at that point. Discontinuities occur when any of these conditions fail. A removable discontinuity exists when the two-sided limit exists but the function is either undefined or...

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Related Experiment Video

Updated: May 20, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

The robustness continuum.

Sasha F Levy1, Mark L Siegal

  • 1Department of Genetics, Stanford University Medical School, Stanford, CA, USA. sflevy@stanford.edu

Advances in Experimental Medicine and Biology
|July 24, 2012
PubMed
Summary
This summary is machine-generated.

Organisms manage environmental and internal changes through robustness, maintaining stable phenotypes or adapting via plasticity. Some use bet-hedging strategies, creating population diversity to survive unpredictable conditions.

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Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting
08:13

Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting

Published on: April 9, 2019

Related Experiment Videos

Last Updated: May 20, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting
08:13

Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting

Published on: April 9, 2019

Area of Science:

  • Evolutionary systems biology
  • Cellular and developmental biology
  • Genetics

Background:

  • Organisms face constant environmental and internal variations.
  • Understanding how life adapts to or exploits variation is key in evolutionary systems biology.
  • Cellular and developmental processes often exhibit high fidelity, producing consistent outcomes despite perturbations.

Purpose of the Study:

  • To explore how living systems cope with environmental and genetic variation.
  • To unify the concepts of high-fidelity robustness and bet-hedging as a continuum.
  • To provide a framework for analyzing regulatory networks underlying fate decisions.

Main Methods:

  • Conceptual framework development.
  • Analysis of robustness and phenotypic plasticity.
  • Examination of bet-hedging as a population-level strategy.

Main Results:

  • Robustness leads to invariant phenotypes or phenotypic plasticity.
  • Low robustness can result in population heterogeneity via bet-hedging.
  • A robustness continuum unifies these responses to variation.

Conclusions:

  • A unifying framework of robustness continuum aids in understanding biological variation.
  • This framework applies to regulatory networks across diverse organisms and diseases like cancer.
  • It offers insights into the evolution of adaptive strategies in complex systems.