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Related Concept Videos

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
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Maxam-Gilbert Sequencing01:05

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
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Per-Unit Sequence Models01:26

Per-Unit Sequence Models

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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.
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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
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Gene Evolution - Fast or Slow?02:05

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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.
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Cyclic Processes And Isolated Systems01:19

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A thermodynamic system with zero heat exchange and work is an isolated system. For these systems, the internal energy remains constant.
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CastNet: a systems-level sequence evolution simulator.

Carlos J Rivera-Rivera1, Djordje Grbic2

  • 1University of Bristol, Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TG, UK. carlos.riverarivera@bristol.ac.uk.

BMC Bioinformatics
|June 12, 2023
PubMed
Summary
This summary is machine-generated.

CastNet simulates genome evolution by linking sequence and regulatory changes, revealing coevolutionary dynamics in gene networks. This new model offers insights into complex evolving systems and molecular evolution.

Keywords:
CoevolutionCoevolutionary websComplex systemsEvo-devoEvolution simulationEvolutionary systemsGene regulatory networks

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Area of Science:

  • Genomics
  • Systems Biology
  • Evolutionary Biology

Background:

  • Traditional DNA evolution simulators are coevolution-agnostic and model single sequences.
  • Biological systems are multi-genic, with gene products influencing each other's evolution.
  • Simulating these crucial coevolutionary dynamics is essential for comparative genomics.

Purpose of the Study:

  • To develop a novel genome evolution simulator, CastNet, that models coevolving regulatory interactions.
  • To explicitly link sequence evolution and regulatory network evolution in a simulation framework.
  • To investigate coevolutionary dynamics within multi-genic systems.

Main Methods:

  • CastNet models genomes as collections of genes with evolving regulatory interactions.
  • Gene regulatory network (GRN) interactions determine phenotype (gene expression profiles) and fitness.
  • A genetic algorithm evolves populations through a user-defined phylogeny, linking regulatory mutations to sequence mutations.

Main Results:

  • CastNet demonstrates a coevolutionary signal among active genes in the GRN.
  • Genes not part of the network exhibit neutral evolution.
  • Selective pressures on regulatory output are reflected in gene sequences, establishing a link between sequence and regulation evolution.

Conclusions:

  • CastNet is a significant advancement for studying genome evolution and complex evolving systems.
  • The simulator provides a new framework for investigating molecular evolution with a focus on sequence coevolution.
  • This approach can yield profound insights into coevolutionary webs.