Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

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...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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.
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,...
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.
In contrast, regions which code...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Double-negative (CD27<sup>-</sup>IgD<sup>-</sup>) B cells are expanded in NSCLC and inversely correlate with affinity-matured B cell populations.

Journal of translational medicine·2018
Same author

Using logistic regression to improve the prognostic value of microarray gene expression data sets: application to early-stage squamous cell carcinoma of the lung and triple negative breast carcinoma.

BMC medical genomics·2014
Same author

Alisertib added to rituximab and vincristine is synthetic lethal and potentially curative in mice with aggressive DLBCL co-overexpressing MYC and BCL2.

PloS one·2014
Same author

In Vitro Assessment of the Inflammatory Breast Cancer Cell Line SUM 149: Discovery of 2 Single Nucleotide Polymorphisms in the RNase L Gene.

Journal of Cancer·2013
Same author

Choosing a method for phylogenetic prediction.

CSH protocols·2011
Same author

Maximum parsimony method for phylogenetic prediction.

CSH protocols·2011
Same journal

Emerging Trends in Mass Spectrometry-Based Quantitative Proteome and Phosphoproteome Profiling in Maize.

Cold Spring Harbor protocols·2026
Same journal

Sample Preparation for Quantitative Proteome and Phosphoproteome Profiling of Maize Tissues.

Cold Spring Harbor protocols·2026
Same journal

High-Throughput Microbial Assay for Amino Acid Measurement in Ground Maize Seed Samples Utilizing Auxotrophic <i>E. coli</i>.

Cold Spring Harbor protocols·2025
Same journal

Grain Quality in Maize.

Cold Spring Harbor protocols·2025
Same journal

High-Throughput Assay for Measuring Phytate and Available Phosphorus in Ground Maize Seed Samples.

Cold Spring Harbor protocols·2025
Same journal

Functional Genomic Analysis of Transposon Insertion Mutant Maize Plants from the UniformMu National Public Resource.

Cold Spring Harbor protocols·2025
See all related articles

Related Experiment Video

Updated: Jun 16, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Using iterative methods for global multiple sequence alignment.

David W Mount

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

    Global sequence alignment for multiple DNA or protein sequences is challenging. This study explores iterative alignment methods, including the Sequence Alignment by Genetic Algorithm (SAGA), to improve accuracy for complex alignments.

    More Related Videos

    A Practical Guide to Phylogenetics for Nonexperts
    12:00

    A Practical Guide to Phylogenetics for Nonexperts

    Published on: February 5, 2014

    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

    Related Experiment Videos

    Last Updated: Jun 16, 2026

    Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
    08:57

    Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

    Published on: August 14, 2018

    A Practical Guide to Phylogenetics for Nonexperts
    12:00

    A Practical Guide to Phylogenetics for Nonexperts

    Published on: February 5, 2014

    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 functional similarities.
    • Traditional dynamic programming methods are computationally intensive and limited to a small number of sequences.
    • Approximate methods are necessary for accurate global alignment of large or diverse sequence sets.

    Purpose of the Study:

    • To review and discuss iterative global alignment methods for multiple sequence alignment.
    • To provide practical steps for implementing the Sequence Alignment by Genetic Algorithm (SAGA) for MSA.

    Main Methods:

    • Discussion of iterative alignment strategies.
    • Detailed explanation of the Sequence Alignment by Genetic Algorithm (SAGA) workflow.
    • Comparative analysis of different iterative approaches (implicitly suggested by the review).

    Main Results:

    • Iterative methods offer a viable approach to overcome limitations of exact algorithms for MSA.
    • SAGA provides a specific, implementable framework for approximate global sequence alignment.
    • The described methods aim to produce more reasonable alignments by refining initial results.

    Conclusions:

    • Iterative global alignment, particularly using methods like SAGA, is essential for complex MSA tasks.
    • These computational approaches enhance the ability to analyze evolutionary and functional aspects of multiple biological sequences.
    • Further exploration of SAGA and similar algorithms can advance bioinformatics research.