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Related Concept Videos

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...
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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

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Related Experiment Video

Updated: Jun 20, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Genomic multiple sequence alignments: refinement using a genetic algorithm.

Chunlin Wang1, Elliot J Lefkowitz

  • 1Department of Microbiology, University of Alabama, Birmingham, Alabama 35294-2170, USA. wangcl@uab.edu

BMC Bioinformatics
|August 10, 2005
PubMed
Summary
This summary is machine-generated.

GenAlignRefine uses a genetic algorithm to improve multiple genomic sequence alignments, enhancing quality by refining poorly aligned regions. This parallelized program refines alignments efficiently, reducing gaps and improving overall sequence data interpretation.

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An Integrated Approach for Microprotein Identification and Sequence Analysis
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Published on: July 12, 2022

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Comparative genomics is crucial for understanding species differences and evolutionary patterns.
  • High-quality genomic sequence alignment is a major challenge in comparative genomics.
  • Existing tools often produce globally correct but locally suboptimal alignments.

Purpose of the Study:

  • To introduce GenAlignRefine, a novel program for improving global multiple sequence alignments.
  • To enhance local alignment quality using a genetic algorithm.
  • To optimize alignment quality by improving the COFFEE score.

Main Methods:

  • GenAlignRefine identifies low-quality alignment regions.
  • Poorly aligned regions are realigned using T-Coffee.
  • A genetic algorithm refines these regions to improve the COFFEE score.
  • The program is implemented in a parallel, cluster-based architecture for efficiency.

Main Results:

  • GenAlignRefine was tested on simulated data and a real dataset of 15 Orthopoxvirus genomes.
  • A 40-processor cluster refined ~200 poorly aligned regions in ~150 minutes.
  • Alignment length decreased by ~1,300 gaps, indicating improved alignment compactness.

Conclusions:

  • A parallelized genetic algorithm effectively optimizes multiple genomic sequence alignments.
  • GenAlignRefine improves alignment quality within a practical timeframe.
  • The approach enhances the utility of comparative genomics analyses.