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Related Concept Videos

Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
Steps in the Modeling Process01:14

Steps in the Modeling Process

Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
Modeling and Similitude01:12

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
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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...

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Related Experiment Video

Updated: Jun 28, 2026

Computer-Generated Animal Model Stimuli
26:43

Computer-Generated Animal Model Stimuli

Published on: July 29, 2007

Modeling sequence evolution.

Pietro Liò1, Martin Bishop

  • 1Computer Laboratory, University of Cambridge, Cambridge, UK.

Methods in Molecular Biology (Clifton, N.J.)
|June 21, 2008
PubMed
Summary
This summary is machine-generated.

This study explores models of biological sequence evolution, focusing on DNA and amino acid changes. It examines how these models reveal species relationships and evolutionary processes using mathematical and statistical methods.

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

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Related Experiment Videos

Last Updated: Jun 28, 2026

Computer-Generated Animal Model Stimuli
26:43

Computer-Generated Animal Model Stimuli

Published on: July 29, 2007

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Area of Science:

  • Molecular Biology
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Biological sequences (DNA, amino acids) encode phylogenetic and evolutionary information.
  • Mathematical and statistical methods are crucial for interpreting this information.
  • Understanding molecular evolution explains the function and divergence of biological molecules.

Purpose of the Study:

  • To describe widely used models of biological sequence evolution.
  • To focus on single nucleotide/amino acid replacement rate models.
  • To discuss modeling evolution at gene and protein module levels.

Main Methods:

  • Review of established models for biological sequence evolution.
  • Analysis of single nucleotide/amino acid replacement rate models.
  • Exploration of gene and protein module level evolutionary modeling.

Main Results:

  • Detailed description of key evolutionary models for DNA and protein sequences.
  • Focus on the mechanisms of nucleotide and amino acid substitutions.
  • Discussion of higher-level evolutionary modeling for genes and protein modules.

Conclusions:

  • Models of molecular evolution are essential for understanding phylogenetic relationships and evolutionary processes.
  • Future research will leverage genomic and proteomic data for advanced molecular evolution studies.