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Related Concept Videos

In-vitro Mutagenesis01:16

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
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...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
In vitro Mutagenesis01:16

In vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
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...

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Related Experiment Video

Updated: Jun 24, 2026

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
08:46

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Published on: December 9, 2015

Simulation and analysis of in vitro DNA evolution.

Morten Kloster1, Chao Tang

  • 1Department of Physics, Princeton University, Princeton, New Jersey 08544, USA.

Physical Review Letters
|February 3, 2004
PubMed
Summary

This study simulates in vitro DNA sequence evolution influenced by transcription factor binding. Researchers identified three distinct evolutionary regimes with unique behaviors, validated by analytical models and simulations.

Area of Science:

  • Molecular Biology
  • Computational Biology
  • Biophysics

Background:

  • Transcription factors regulate gene expression by binding to specific DNA sequences.
  • Understanding the evolutionary dynamics of DNA-protein interactions is crucial for deciphering biological regulation.

Purpose of the Study:

  • To theoretically investigate the in vitro evolution of DNA sequences under transcription factor binding.
  • To model and simulate the evolutionary process using realistic parameters.

Main Methods:

  • Developed a theoretical model for protein-DNA binding.
  • Utilized available binding constants for the Mnt protein.
  • Performed large-scale, realistic simulations of DNA sequence evolution.
  • Derived analytical estimates for evolutionary regimes.

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Last Updated: Jun 24, 2026

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
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Published on: December 9, 2015

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Published on: September 20, 2016

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Main Results:

  • Identified three distinct evolutionary regimes with unique behaviors.
  • Analytical estimates showed good agreement with simulation results.
  • Demonstrated the impact of DNA-protein interaction details on evolutionary outcomes.

Conclusions:

  • The study provides a theoretical framework for understanding DNA sequence evolution driven by transcription factor binding.
  • The identified regimes and validated models offer insights into evolutionary dynamics.
  • Highlights the importance of specific molecular interactions in shaping sequence evolution.