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

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

19.9K
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.
19.9K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.6K
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...
6.6K
Genomics02:02

Genomics

38.8K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
38.8K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

8.7K
While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
8.7K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

3.0K
3.0K

You might also read

Related Articles

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

Sort by
Same author

The 3D genomics of lampbrush chromosomes highlights the role of active transcription in chromatin organization.

Nucleic acids research·2026
Same author

Divergent immune strategies of Colorado potato beetle larvae against the entomopathogenic fungi Metarhizium robertsii and Beauveria bassiana: A comparative transcriptomic analysis.

Insect molecular biology·2026
Same author

Zooming into rearranged genome: applying pipeline of cytological, genomic, and transcriptomic methods for structural variant interpretation.

Molecular omics·2026
Same author

Chromatin landscape, transcriptomic and ChIP-seq profiling of Anopheles stephensi MSQ43 cell line.

Scientific data·2025
Same author

Direction and modality of transcription changes caused by TAD boundary disruption in Slc29a3/Unc5b locus depends on tissue-specific epigenetic context.

Epigenetics & chromatin·2025
Same author

Charm is a flexible pipeline to simulate chromosomal rearrangements on Hi-C-like data.

NAR genomics and bioinformatics·2025

Related Experiment Video

Updated: Nov 18, 2025

3D Multicolor DNA FISH Tool to Study Nuclear Architecture in Human Primary Cells
11:25

3D Multicolor DNA FISH Tool to Study Nuclear Architecture in Human Primary Cells

Published on: January 25, 2020

10.6K

Predicting Genome Architecture: Challenges and Solutions.

Polina Belokopytova1,2, Veniamin Fishman1,2

  • 1Natural Sciences Department, Novosibirsk State University, Novosibirsk, Russia.

Frontiers in Genetics
|February 8, 2021
PubMed
Summary

This review explores reconstructing genome architecture from epigenetic data. It covers biophysical and statistical models, discussing their strengths and limitations for understanding gene regulation and structural variations.

Keywords:
Hi-Cmachine learningmodelingpolymer physicspredicting approaches

More Related Videos

Mapping Mammalian 3D Genome Interactions with Micro-C-XL
11:41

Mapping Mammalian 3D Genome Interactions with Micro-C-XL

Published on: November 3, 2023

3.2K
Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.
22:27

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Published on: May 6, 2010

410.5K

Related Experiment Videos

Last Updated: Nov 18, 2025

3D Multicolor DNA FISH Tool to Study Nuclear Architecture in Human Primary Cells
11:25

3D Multicolor DNA FISH Tool to Study Nuclear Architecture in Human Primary Cells

Published on: January 25, 2020

10.6K
Mapping Mammalian 3D Genome Interactions with Micro-C-XL
11:41

Mapping Mammalian 3D Genome Interactions with Micro-C-XL

Published on: November 3, 2023

3.2K
Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.
22:27

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

Published on: May 6, 2010

410.5K

Area of Science:

  • Genomics
  • Epigenetics
  • Computational Biology

Background:

  • Genome architecture is crucial for gene regulation.
  • High-throughput methods generate extensive data on genome organization.
  • Connecting genome structure with epigenetic marks requires advanced models.

Purpose of the Study:

  • To review methods for reconstructing chromatin architecture from epigenetic data.
  • To discuss the utility and constraints of biophysical and statistical approaches.
  • To highlight new predictive methods for assessing structural variations.

Main Methods:

  • Review of biophysical modeling approaches.
  • Review of statistical modeling approaches.
  • Discussion of predictive modeling for structural variations.

Main Results:

  • Epigenetic data can be used to infer chromatin architecture.
  • Biophysical and statistical models offer insights but have limitations.
  • Emerging predictive methods aid in scoring structural variation effects.

Conclusions:

  • Reconstructing genome architecture from epigenetic data is feasible using various models.
  • Understanding chromatin organization mechanisms benefits from these computational approaches.
  • Predictive models show promise for analyzing structural variations in human genomics.