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

Synthetic Biology02:55

Synthetic Biology

4.7K
Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
4.7K
Genomics02:02

Genomics

36.3K
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...
36.3K
Protein Networks02:26

Protein Networks

3.9K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.9K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.8K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
4.8K
The Tree of Life - Bacteria, Archaea, and Eukaryotes02:40

The Tree of Life - Bacteria, Archaea, and Eukaryotes

13.9K
13.9K
Types of Genetic Transfer Between Organisms02:18

Types of Genetic Transfer Between Organisms

27.8K
Genetic transfer occurs when genetic information is passed from one organism to another. It occurs via two mechanisms: vertical gene transfer and horizontal gene transfer. Vertical gene transfer occurs when genetic information is transferred from one generation to the next, which happens much more frequently than horizontal gene transfer. Both sexual and asexual reproduction are forms of vertical gene transfer, where one or more organisms pass some or all of their genome onto their progeny.
27.8K

You might also read

Related Articles

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

Sort by
Same author

Evaluating completeness, coherence, and consistency of genome-scale function annotations.

Briefings in bioinformatics·2026
Same author

A pragmatist approach to bridging tables and ontologies through LinkML and punning.

Journal of biomedical semantics·2026
Same author

MiRInter-Trans: a transformer-based framework for microRNA interaction prediction.

Bioinformatics advances·2026
Same author

In-depth Human Phenotype Ontology Curation Boosts Prioritization Performance for Netherton Syndrome.

The British journal of dermatology·2026
Same author

The HuBMAP Framework for Advancing Data FAIRness.

bioRxiv : the preprint server for biology·2026
Same author

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology·2026
Same journal

Dataset of Optimized Structures of Aliphatic Chains Chemisorbed on Si(110) and Si(111) Surfaces via First-Principles Methods.

Scientific data·2026
Same journal

EURO-PROBE - Manual segmentations of the prostate and intraprostatic urethra on T2-weighted MRI.

Scientific data·2026
Same journal

Chromosome-Level Genome Assembly of Southern Africa Mozambique Tilapia (Oreochromis mossambicus) using PacBio HiFi and Omni-C sequencing.

Scientific data·2026
Same journal

Ovarian Stainology: Database of evidence-based immunohistochemical antigen expression in ovarian tumors.

Scientific data·2026
Same journal

A dataset of small protein conformational ensembles from all-atom molecular dynamics simulations.

Scientific data·2026
Same journal

A real-world Fitbit-derived dataset of activity, sleep, and heart rate with matched clinical factors in on-treatment lung cancer patients.

Scientific data·2026
See all related articles

Related Experiment Video

Updated: Jun 28, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K

An open source knowledge graph ecosystem for the life sciences.

Tiffany J Callahan1,2, Ignacio J Tripodi3, Adrianne L Stefanski4

  • 1Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA. tiffany.callahan@cuanschutz.edu.

Scientific Data
|April 11, 2024
PubMed
Summary
This summary is machine-generated.

PheKnowLator automates the FAIR construction of phenotype knowledge graphs (KGs) with customizable representations. This semantic ecosystem addresses biomedical data integration challenges, offering flexibility without sacrificing performance or usability.

More Related Videos

A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

17.6K
Development of Compendium for Esophageal Squamous Cell Carcinoma
03:36

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

407

Related Experiment Videos

Last Updated: Jun 28, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K
A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

17.6K
Development of Compendium for Esophageal Squamous Cell Carcinoma
03:36

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

407

Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Data Science

Background:

  • Translational research necessitates integrating biological data across multiple scales.
  • Advances in multi-omics and sequencing generate vast datasets, posing significant integration challenges.
  • Existing knowledge graph (KG) construction methods offer limited flexibility in knowledge representation for complex biomedical problems.

Purpose of the Study:

  • To introduce PheKnowLator, a semantic ecosystem for automated, FAIR (Findable, Accessible, Interoperable, Reusable) KG construction.
  • To provide a fully customizable knowledge representation framework for biomedical KGs.
  • To address limitations in existing KG construction tools regarding flexibility and choice.

Main Methods:

  • Developed PheKnowLator as a semantic ecosystem with KG construction resources, analysis tools, and benchmarks.
  • Included data preparation APIs, SPARQL endpoint resources, and abstraction algorithms.
  • Designed for fully customizable knowledge representation in ontologically grounded KGs.

Main Results:

  • Evaluated PheKnowLator against existing open-source KG construction methods.
  • Analyzed computational performance using 12 large-scale KG construction tasks.
  • Demonstrated that PheKnowLator enables fully customizable KGs with maintained performance and usability.

Conclusions:

  • PheKnowLator offers a flexible and automated approach to constructing FAIR biomedical knowledge graphs.
  • The ecosystem supports customizable knowledge representation, overcoming limitations of existing tools.
  • PheKnowLator enhances the integration of multi-omics data for translational research.