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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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...
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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.
In contrast, regions which code...
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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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What is Gene Expression?01:42

What is Gene Expression?

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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
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What is Gene Expression?01:36

What is Gene Expression?

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A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
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What is Gene Expression?01:42

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Related Experiment Video

Updated: Apr 30, 2026

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

8.3K

Evolutionary approach for relative gene expression algorithms.

Marcin Czajkowski1, Marek Kretowski1

  • 1Faculty of Computer Science, Bialystok University of Technology, Wiejska 45a, 15-351 Białystok, Poland.

Thescientificworldjournal
|May 3, 2014
PubMed
Summary
This summary is machine-generated.

A novel evolutionary algorithm, EvoTSP, enhances relative expression analysis for gene classification. It improves accuracy and explores more gene relationships than traditional methods.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Gene Expression Analysis

Background:

  • Relative Expression Analysis (RXA) is used for gene classification with microarray data.
  • Current RXA methods require feature selection and have restrictive assumptions due to computational complexity.
  • Exploring all gene subsets is computationally infeasible for traditional RXA.

Purpose of the Study:

  • To develop a specialized evolutionary algorithm (EA) for identifying advanced gene relations.
  • To unify major variants of relative expression algorithms.
  • To improve the accuracy and scope of gene expression analysis.

Main Methods:

  • Developed EvoTSP, a specialized evolutionary algorithm for top-scoring pairs.
  • Unified existing relative expression algorithms using the EA framework.
  • Introduced weighted top-scoring pairs to enhance analysis.

Main Results:

  • EvoTSP significantly outperforms existing relative expression algorithms in accuracy.
  • The algorithm allows for exploration of a much larger solution space.
  • Successfully unified major RXA variants through the EA approach.

Conclusions:

  • EvoTSP offers a more advanced and accurate method for gene expression analysis.
  • The evolutionary algorithm approach overcomes limitations of traditional RXA.
  • This method provides a unified framework for relative expression analysis.