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

Genomics02:02

Genomics

40.7K
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...
40.7K
Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

37.2K
Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
37.2K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

9.1K
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.
9.1K
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

16.3K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
16.3K
Genomic DNA in Prokaryotes00:46

Genomic DNA in Prokaryotes

48.7K
The genome of most prokaryotic organisms consists of double-stranded DNA organized into one circular chromosome in a region of cytoplasm called the nucleoid. The chromosome is tightly wound, or supercoiled, for efficient storage. Prokaryotes also contain other circular pieces of DNA called plasmids. These plasmids are smaller than the chromosome and often carry genes that confer adaptive functions, such as antibiotic resistance.
Genomic Diversity in Bacteria
Although bacterial genomes are much...
48.7K
Genomic DNA in Eukaryotes00:58

Genomic DNA in Eukaryotes

53.0K
Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
53.0K

You might also read

Related Articles

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

Sort by
Same author

Artificial intelligence in pathology: a framework for preserving brain capital in the diagnostic apex.

Croatian medical journal·2026
Same author

The survival double descent: generalization dynamics of deep neural networks in time-to-event analysis.

BMC medical research methodology·2026
Same author

The CARE framework for AI dataset documentation in clinical laboratories: a comprehensive checklist and data lineage methodology.

American journal of clinical pathology·2026
Same author

Agent-based large language model system for extracting structured data from breast cancer synoptic reports: a dual-validation study.

JAMIA open·2026
Same author

Genomic and Immune Landscape of Pancreatic Ductal Adenocarcinoma Associated with Germline Pathogenic Variants in ATM.

Clinical cancer research : an official journal of the American Association for Cancer Research·2025
Same author

Establishing a comprehensive artificial intelligence lifecycle framework for laboratory medicine and pathology: A series introduction.

American journal of clinical pathology·2025

Related Experiment Video

Updated: Feb 5, 2026

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
08:31

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

Published on: May 26, 2013

11.5K

Will Digital Pathology be as Disruptive as Genomics?

Steven N Hart1

  • 1Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.

Journal of Pathology Informatics
|September 1, 2018
PubMed
Summary

Digital pathology digitizes traditional assessments, enabling AI-driven quantitative analysis from whole slide images. Lessons from the genomics revolution can accelerate this computational pathology transition.

Keywords:
Genomicsbioinformaticsdigital pathology

More Related Videos

Symmetric Bihemispheric Postmortem Brain Cutting to Study Healthy and Pathological Brain Conditions in Humans
08:29

Symmetric Bihemispheric Postmortem Brain Cutting to Study Healthy and Pathological Brain Conditions in Humans

Published on: December 18, 2016

14.6K
Assessment of Oxidative Damage in the Primary Mouse Ocular Surface Cells/Stem Cells in Response to Ultraviolet-C UV-C Damage
12:59

Assessment of Oxidative Damage in the Primary Mouse Ocular Surface Cells/Stem Cells in Response to Ultraviolet-C UV-C Damage

Published on: February 15, 2020

6.7K

Related Experiment Videos

Last Updated: Feb 5, 2026

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
08:31

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

Published on: May 26, 2013

11.5K
Symmetric Bihemispheric Postmortem Brain Cutting to Study Healthy and Pathological Brain Conditions in Humans
08:29

Symmetric Bihemispheric Postmortem Brain Cutting to Study Healthy and Pathological Brain Conditions in Humans

Published on: December 18, 2016

14.6K
Assessment of Oxidative Damage in the Primary Mouse Ocular Surface Cells/Stem Cells in Response to Ultraviolet-C UV-C Damage
12:59

Assessment of Oxidative Damage in the Primary Mouse Ocular Surface Cells/Stem Cells in Response to Ultraviolet-C UV-C Damage

Published on: February 15, 2020

6.7K

Area of Science:

  • Digital pathology
  • Computational pathology
  • Artificial intelligence in pathology

Background:

  • Traditional histochemical analysis, like H&E staining, has seen minimal change for over a century.
  • The field of pathology is undergoing a digital transformation, moving towards digital pathology.
  • Digitization of whole slide images is a key enabler for advanced computational analysis.

Purpose of the Study:

  • To explore the parallels between the digital transition in pathology and the genomics revolution.
  • To identify key lessons from genomics to optimize the adoption of digital pathology.
  • To prevent historical delays and challenges in the computational pathology advancement.

Main Methods:

  • Comparative analysis of computational infrastructure and data handling in genomics and digital pathology.
  • Review of historical challenges and successes in the genomics data revolution.
  • Identification of transferable strategies for digital pathology implementation.

Main Results:

  • Significant similarities exist in the computational and infrastructural challenges faced by both genomics and digital pathology.
  • The transition to digital pathology offers a similar potential for revolutionizing qualitative assessments into quantitative insights.
  • Lessons from genomics highlight the importance of data standardization, scalable infrastructure, and AI integration.

Conclusions:

  • Digital pathology, empowered by whole slide imaging and AI, promises to transform pathology from qualitative to quantitative.
  • Applying lessons learned from the genomics revolution can significantly accelerate the successful implementation of digital pathology.
  • Proactive planning regarding computational infrastructure and data management is crucial for realizing the full potential of digital pathology.