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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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Updated: Jun 16, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

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Published on: February 5, 2014

Comparing programs and methods to use for global multiple sequence alignment.

David W Mount

    Cold Spring Harbor Protocols
    |February 12, 2010
    PubMed
    Summary
    This summary is machine-generated.

    Finding optimal multiple sequence alignment is complex. Approximate methods like progressive alignment and graph-based approaches are essential for analyzing sequence variations and building phylogenetic trees.

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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Optimal global alignment of multiple sequences (more than three) is computationally challenging.
    • Existing methods struggle to simultaneously account for matches, mismatches, and gaps across all sequences.
    • Approximate methods are necessary for practical multiple sequence alignment.

    Purpose of the Study:

    • To review and compare various approximate methods for multiple sequence alignment.
    • To evaluate the utility of different alignment strategies under diverse conditions.
    • To discuss techniques for clustering sequences and constructing phylogenetic trees from large datasets.

    Main Methods:

    • Progressive global alignment
    • Iterative global alignment
    • Alignment based on conserved patterns
    • Statistical methods for probabilistic modeling
    • Graph-based multiple sequence alignment methods
    • Pairwise sequence similarity calculation for large datasets

    Main Results:

    • Approximate methods are widely used due to the complexity of optimal alignment.
    • Sequence similarity analysis is a common first step for comparing 10 or more sequences.
    • Various methods exist for sequence clustering and phylogenetic tree construction.

    Conclusions:

    • Approximate methods are crucial for effective multiple sequence alignment.
    • The choice of method depends on the specific dataset and research question.
    • Understanding sequence similarity aids in grouping related sequences and inferring evolutionary relationships.