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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...
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.
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,...
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...
Gene Conversion02:08

Gene Conversion

Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...

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Updated: Jun 27, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

GeNESiS: gene network evolution simulation software.

Anton Kratz1, Masaru Tomita, Arun Krishnan

  • 1Institute for Advanced Biosciences, Keio University, 14-1, Baba-Cho, Tsuruoka, Yamagata-ken, 997-0035, Japan. anton.kratz@gmail.com

BMC Bioinformatics
|December 18, 2008
PubMed
Summary
This summary is machine-generated.

GeNESiS models gene regulatory network (GRN) evolution using a genetic algorithm. This software helps researchers understand how GRNs evolve under various conditions and selective pressures.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Evolutionary Biology

Background:

  • Gene Regulatory Networks (GRNs) are crucial for cellular function, yet their evolutionary origins remain poorly understood.
  • Previous work established a framework for analyzing GRN evolution, focusing on robustness under different parameters.
  • Significant interest exists in modeling and simulating GRN evolution to uncover underlying mechanisms.

Purpose of the Study:

  • To introduce GeNESiS, a parallel software package for simulating the evolution of Gene Regulatory Networks (GRNs).
  • To provide a tool for researchers to investigate the evolutionary dynamics of GRNs.
  • To enable the study of GRN evolution under diverse selective pressures and initial conditions.

Main Methods:

  • GeNESiS combines finite-state and stochastic models for gene regulation.
  • It simulates GRN evolution using a genetic algorithm, representing network connections as binary strings.
  • The software facilitates simulations under varying selective pressures and starting populations.

Main Results:

  • The developed software package, GeNESiS, enables parallel modeling and simulation of GRN evolution.
  • It allows for the exploration of evolutionary trajectories of GRNs.
  • The tool supports the investigation of how different conditions impact GRN evolution.

Conclusions:

  • GeNESiS is a valuable tool for scientists studying the evolution of gene regulatory networks.
  • It aids in understanding GRN evolution under various conditions and selective pressures.
  • Modeling GRN evolution with GeNESiS can enhance comprehension of their network characteristics.