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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...
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

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.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...
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.
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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.
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Microbial Phylogeny01:28

Microbial Phylogeny

Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.The length of the branches can depict time or the relative amount of change among organisms. For instance, the branch length might indicate the number of amino acid changes in the sequence that underlies the...

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

A space-efficient algorithm for three sequence alignment and ancestor inference.

Feng Yue1, Jijun Tang

  • 1Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA. yuef@engr.sc.edu

International Journal of Data Mining and Bioinformatics
|June 13, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel algorithm for aligning biological sequences and reconstructing ancestral sequences, offering improved accuracy and reduced memory usage compared to existing tools.

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Last Updated: Jun 22, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Multiple sequence alignment (MSA) is crucial for understanding evolutionary relationships and inferring ancestral sequences.
  • Existing MSA algorithms often face challenges with memory efficiency and alignment accuracy, particularly for larger datasets.
  • Inferring ancestral sequences provides insights into evolutionary history and gene function.

Purpose of the Study:

  • To develop a novel, memory-efficient algorithm for simultaneous alignment of three biological sequences.
  • To accurately infer the common ancestral sequence using an affine gap model.
  • To enhance the performance of multiple sequence alignment and ancestral sequence reconstruction.

Main Methods:

  • A novel algorithm employing a divide-and-conquer strategy for memory reduction from O(n3) to O(n2).
  • Dynamic programming approach to guarantee optimal alignment.
  • Implementation and extensive testing using the BAliBASE dataset and Random Model of Sequence Evolution (ROSE) simulated data.

Main Results:

  • The proposed algorithm achieves significant memory usage reduction.
  • Demonstrated superior alignment accuracy compared to established tools like ClustalW and T-Coffee.
  • Produced more accurate ancestral sequences than existing popular multiple sequence alignment tools.

Conclusions:

  • The novel algorithm offers a more efficient and accurate solution for multiple sequence alignment and ancestral sequence reconstruction.
  • The divide-and-conquer strategy effectively addresses memory limitations in sequence alignment.
  • This method advances the field of bioinformatics by providing a powerful tool for evolutionary analysis.