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

Improving Translational Accuracy02:07

Improving Translational Accuracy

3.4K
3.4K
Improving Translational Accuracy02:07

Improving Translational Accuracy

13.9K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
13.9K
Associative Learning01:27

Associative Learning

1.1K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
1.1K
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

20.4K
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.
20.4K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.8K
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...
6.8K
Introduction to Learning01:18

Introduction to Learning

832
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
832

You might also read

Related Articles

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

Sort by
Same author

Epidemic Question Answering: question generation and entailment for Answer Nugget discovery.

Journal of the American Medical Informatics Association : JAMIA·2022
Same author

Adaptation and Dissemination of a National Cancer Institute HPV Vaccine Evidence-Based Cancer Control Program to the Social Media Messaging Environment.

Frontiers in digital health·2022
Same author

Scaling up the discovery of hesitancy profiles by identifying the framing of beliefs towards vaccine confidence in Twitter discourse.

Journal of behavioral medicine·2022
Same author

Automatic detection of COVID-19 vaccine misinformation with graph link prediction.

Journal of biomedical informatics·2021
Same author

The impact of learning Unified Medical Language System knowledge embeddings in relation extraction from biomedical texts.

Journal of the American Medical Informatics Association : JAMIA·2020
Same author

Active deep learning for the identification of concepts and relations in electroencephalography reports.

Journal of biomedical informatics·2019

Related Experiment Video

Updated: Dec 23, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.1K

Bootstrapping Adversarial Learning of Biomedical Ontology Alignments.

Ramon M Maldonado1, Sanda M Harabagiu1

  • 1University of Texas at Dallas, Richardson, TX, U.S.A.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|April 21, 2020
PubMed
Summary

This study introduces KAEGAN, a novel approach for aligning biomedical ontologies using knowledge graph embeddings. Jointly learning alignment and representation enhances performance over isolated methods.

More Related Videos

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

2.0K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

921

Related Experiment Videos

Last Updated: Dec 23, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.1K
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

2.0K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

921

Area of Science:

  • Biomedical Informatics
  • Artificial Intelligence
  • Knowledge Representation

Background:

  • Automatic alignment of biomedical ontologies is crucial due to their increasing complexity and widespread use.
  • Neural learning techniques can leverage knowledge graph embeddings for ontology representation and alignment.

Purpose of the Study:

  • To present the Knowledge-graph Alignment & Embedding Generative Adversarial Network (KAEGAN).
  • To demonstrate KAEGAN's capability in representing relational knowledge and aligning biomedical ontologies using semantics.

Main Methods:

  • KAEGAN utilizes a Generative Adversarial Network (GAN) framework.
  • The model is trained using bootstrapping for iterative alignment improvement.
  • It learns knowledge embeddings from distinct biomedical ontologies.

Main Results:

  • Experimental results indicate promising performance for KAEGAN.
  • Jointly learning ontology alignment and knowledge representation yields superior outcomes.
  • The approach effectively utilizes ontology semantics for alignment.

Conclusions:

  • KAEGAN offers a promising method for automated biomedical ontology alignment.
  • Integrating knowledge representation with alignment learning enhances overall effectiveness.
  • This work advances the field of biomedical knowledge graph integration.