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

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

687
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
687
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

8.7K
Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
8.7K
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.5K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.5K
X-linked Traits01:19

X-linked Traits

58.3K
In most mammalian species, females have two X sex chromosomes and males have an X and Y. As a result, mutations on the X chromosome in females may be masked by the presence of a normal allele on the second X. In contrast, a mutation on the X chromosome in males more often causes observable biological defects, as there is no normal X to compensate. Trait variations arising from mutations on the X chromosome are called “X-linked”.
58.3K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.4K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.4K
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

924
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
924

You might also read

Related Articles

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

Sort by
Same author

Data harmonization processes of cancer data into the observational medical outcomes partnership common data model.

Scientific reports·2026
Same author

Aspects Supporting and Hindering Type 2 Diabetes Self-Management in Web-Based Educational Portals: Usability Testing Study With Updated Framework in Razavi-Khorasan, Iran.

JMIR human factors·2026
Same author

Exploring Medical Information Needs and Accessibility in Swedish Dental Care by Analysis of Documentation Workflows and Electronic Dental Records in Dalarna: Sociotechnical Qualitative Study.

JMIR human factors·2026
Same author

Exploring the Impact of the COVID-19 Pandemic on Learning Experience, Mental Health, Adaptability, and Resilience Among Health Informatics Master's Students: Focus Group Study.

JMIR medical education·2025
Same author

Development Process for Type 2 Diabetes Patient Applications: Findings from a Literature Review.

Studies in health technology and informatics·2024
Same author

Enhancing Women's Health: An Assessment of Data Privacy and Security of Menopause FemTech Applications.

Studies in health technology and informatics·2023

Related Experiment Video

Updated: Jan 20, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.2K

Linked Open Data in the Biomedical Information Area: A Keywords Analysis.

Stefano Bonacina1

  • 1Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden.

Studies in Health Technology and Informatics
|August 24, 2019
PubMed
Summary

This study analyzed Linked Open Data usage in biomedical literature. Findings reveal limited keyword diversity, with most terms appearing only once, suggesting underutilization.

Keywords:
Review Literature as TopicSemantic Web

More Related Videos

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

1.3K
Generation of Alginate Microspheres for Biomedical Applications
10:33

Generation of Alginate Microspheres for Biomedical Applications

Published on: August 12, 2012

21.7K

Related Experiment Videos

Last Updated: Jan 20, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.2K
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

1.3K
Generation of Alginate Microspheres for Biomedical Applications
10:33

Generation of Alginate Microspheres for Biomedical Applications

Published on: August 12, 2012

21.7K

Area of Science:

  • Biomedical Informatics
  • Bibliometrics
  • Data Science

Background:

  • Linked Open Data (LOD) offers significant potential for data integration and discovery in the biomedical field.
  • Understanding the current adoption of LOD principles in published research is crucial for assessing its impact and identifying barriers.

Purpose of the Study:

  • To quantify the extent of Linked Open Data usage within the biomedical literature.
  • To identify and categorize keywords associated with LOD in this domain.

Main Methods:

  • A systematic literature review was conducted following the PRISMA statement guidelines.
  • Forty-six relevant papers were analyzed to extract and identify keywords.
  • Keywords were classified using Medical Subject Headings (MeSH) categories where applicable.

Main Results:

  • A total of 169 unique keywords were identified across the 46 papers.
  • Twenty-three keywords appeared more than once, while 146 keywords were unique to a single paper.
  • Two MeSH categories were identified as recurring themes in the analyzed literature.

Conclusions:

  • The current usage of Linked Open Data in biomedical literature appears limited, characterized by a low frequency of recurring keywords.
  • Further research, including the application of association rule learning to keywords, is recommended to explore relationships and potential patterns.