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

Synteny and Evolution02:31

Synteny and Evolution

3.9K
John H. Renwick first coined the term “synteny” in 1971, which refers to the genes present on the same chromosomes, even if they are not genetically linked. The species with common ancestry tend to show conserved syntenic regions. Therefore, the concept of synteny is nowadays used to describe the evolutionary relationship between species.
Around 80 million years ago, the human and mice lineages diverged from the common ancestor. During the course of evolution, the ancestral...
3.9K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

7.1K
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...
7.1K
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

8.1K
The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are...
8.1K
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

12.1K
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
12.1K
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

4.9K
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...
4.9K
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

21.3K
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.
21.3K

You might also read

Related Articles

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

Sort by
Same author

Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal.

Bioinformatics and biology insights·2021
Same author

PLIDflow: an open-source workflow for the online analysis of protein-ligand docking using galaxy.

Bioinformatics (Oxford, England)·2020
Same author

Ultra-fast genome comparison for large-scale genomic experiments.

Scientific reports·2019
Same author

Combining Strengths for Multi-genome Visual Analytics Comparison.

Bioinformatics and biology insights·2019
Same author

Training bioinformaticians in High Performance Computing.

Heliyon·2018
Same author

Precise and Parallel Pairwise Metagenomic Comparisons.

Journal of computational biology : a journal of computational molecular cell biology·2018
Same journal

Investigating Effect of Dimensional Variance on Separation of Glomerular Ultrafiltrate in a Microfluidic Environment.

IEEE transactions on nanobioscience·2026
Same journal

Green synthesis of multifunctional ZnFe<sub>2</sub>O<sub>4</sub>-MWCNT-Cellulose acetate nanocomposite for peroxidase enzyme immobilization.

IEEE transactions on nanobioscience·2026
Same journal

IoT-Enabled SnOâ‚‚-Based Humidity Sensor for Real-Time Monitoring in Neonatal Incubators.

IEEE transactions on nanobioscience·2026
Same journal

Electrokinetic and Antibiofilm Effects of Silver Nanoparticles Combined with Imipenem Against multidrug-resistant of Klebsiella pneumoniae.

IEEE transactions on nanobioscience·2026
Same journal

Bio-inspired Optofluidic Molecular Communication with Photothermally Actuated Microrobot Swarms.

IEEE transactions on nanobioscience·2026
Same journal

Nanostructured ZnO Thin Film-Based Enzymatic Biosensor for Sensitive Acetylcholine Detection in Neurological Applications.

IEEE transactions on nanobioscience·2026
See all related articles

Related Experiment Video

Updated: Mar 8, 2026

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

4.0K

Computational Synteny Block: A Framework to Identify Evolutionary Events.

Jose Antonio Arjona-Medina, Oswaldo Trelles

    IEEE Transactions on Nanobioscience
    |January 24, 2017
    PubMed
    Summary
    This summary is machine-generated.

    Identifying large genomic rearrangements is key for evolutionary studies. Current tools often have limitations, necessitating new methods for accurate breakpoint identification and analysis of evolutionary events.

    More Related Videos

    Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
    09:14

    Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

    Published on: June 28, 2018

    7.6K
    Rare Event Detection Using Error-corrected DNA and RNA Sequencing
    10:36

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing

    Published on: August 3, 2018

    12.6K

    Related Experiment Videos

    Last Updated: Mar 8, 2026

    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

    4.0K
    Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
    09:14

    Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

    Published on: June 28, 2018

    7.6K
    Rare Event Detection Using Error-corrected DNA and RNA Sequencing
    10:36

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing

    Published on: August 3, 2018

    12.6K

    Area of Science:

    • Genomics
    • Bioinformatics
    • Evolutionary Biology

    Background:

    • Accurate identification of large genomic rearrangements is crucial for understanding evolutionary events and defining breakpoints.
    • Existing software tools for this task often have limitations, including reliance on pre-computed data, focus on protein-level analysis, complex parameter tuning, or difficulty handling repetitive regions.

    Purpose of the Study:

    • To address the limitations of current software for identifying large genomic rearrangements.
    • To develop a more effective method for detecting genomic rearrangements and their breakpoints.

    Main Methods:

    • The study likely involves developing or evaluating a novel computational approach for genomic rearrangement identification.
    • This may include algorithms that do not rely on pre-computed High-scoring Segment Pairs (HSPs) or gene annotations and can analyze non-coding regions.
    • The method aims to simplify the process, potentially by better handling duplications and repeats.

    Main Results:

    • The abstract does not contain specific results, but implies the development of a tool or method that overcomes the limitations mentioned in the background.
    • The new method is expected to improve the accuracy and efficiency of identifying large genomic rearrangements and breakpoints.

    Conclusions:

    • There is a need for improved bioinformatics tools to accurately identify large genomic rearrangements.
    • The proposed approach aims to overcome the shortcomings of existing methods, facilitating the study of genome evolution.