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

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications09:20

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

9.2K
We present a protocol and associated programming code as well as metadata samples to support a cloud-based automated identification of phrases-category association representing unique concepts in user selected knowledge domain in biomedical literature. The phrase-category association quantified by this protocol can facilitate in depth analysis in the selected knowledge...
9.2K
Crowding10:23

Crowding

6.3K
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University
Human vision depends on light-sensitive neurons that are arranged in the back of the eye on a tissue called the retina. The neurons, called the rods and cones because of their shapes, are not uniformly distributed on the retina. Instead, there is a region in the center of the retina called the macula where cones are densely packed, and especially so in a central sub-region of the macula called the fovea. Outside the fovea there...
6.3K
Data Source01:28

Data Source

823
Data sources are fundamental for accurate information gathering and can be primary, like experiments and surveys, or secondary, such as literature reviews. They can also be qualitative, like interviews offering deep insights, or quantitative, like surveys providing numerical data for analysis.
Ensuring the reliability and validity of data sources is crucial. Reliable sources consistently produce accurate results, and valid sources measure what they intend to. For example, a well-constructed...
823
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

757
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
757
Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding09:14

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

12.9K
We present a protocol to obtain cell-derived matrices rich in extracellular matrix proteins, using macromolecular crowders (MMC). In addition, we present a protocol which incorporates MMC in 3D organotypic skin co-culture generation, which reduces culture time while maintaining maturity of...
12.9K
Fixed Target Serial Data Collection at Diamond Light Source06:19

Fixed Target Serial Data Collection at Diamond Light Source

3.8K
We present a comprehensive guide to fixed target sample preparation, data collection, and data processing for serial synchrotron crystallography at Diamond beamline I24.
3.8K

You might also read

Related Articles

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

Sort by
Same author

Mechanically Interlocked Indigo Photoswitches.

Angewandte Chemie (International ed. in English)·2026
Same author

Towards a decentralized future for open-science databases.

Nature genetics·2026
Same author

Serial Spatial Transcriptomics Reveal Divergent Routes to Therapy Resistance in Metastatic Breast Cancer.

Research square·2026
Same author

Erratum: Placental epigenetic clocks derived from crowdsourcing: Implications for the study of accelerated aging in obstetrics.

iScience·2026
Same author

Benchmarking large language models for predictive modeling in biomedical research with a focus on reproductive health.

Cell reports. Medicine·2026
Same author

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Cell reports. Medicine·2025

Related Experiment Video

Updated: Jan 19, 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

Reproducible biomedical benchmarking in the cloud: lessons from crowd-sourced data challenges.

Kyle Ellrott1, Alex Buchanan1, Allison Creason1

  • 1Biomedical Engineering, Oregon Health and Science University, Portland, OR, 97239, USA.

Genome Biology
|September 12, 2019
PubMed
Summary

Biomedical data challenges face reproducibility issues due to diverse software and formats. Innovative solutions like cloud-ready packages and crowd-sourced benchmarking are improving quantitative analysis and tool assessment.

More Related Videos

Investigating Crowding in Peripheral Vision
10:23

Investigating Crowding in Peripheral Vision

Published on: April 30, 2023

6.3K
Data Source
01:28

Data Source

823

Related Experiment Videos

Last Updated: Jan 19, 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
Investigating Crowding in Peripheral Vision
10:23

Investigating Crowding in Peripheral Vision

Published on: April 30, 2023

6.3K
Data Source
01:28

Data Source

823

Area of Science:

  • Biomedical data analysis
  • Computational biology
  • Bioinformatics

Background:

  • Ensuring reproducibility and reusability in biomedical data challenges is hindered by diverse software architectures, file formats, and computing environments.
  • Broad acceptance for addressing complex biomedical questions and enabling robust tool assessment remains a significant hurdle.

Discussion:

  • Recent data challenges are adopting innovative approaches, including virtualization and cloud-ready software packages, to enhance model reproducibility.
  • Leveraging crowd-sourced benchmarking challenges offers a scalable solution for evaluating quantitative biomedical data analysis methods.

Key Insights:

  • Virtualization and cloud computing are crucial for standardizing computational environments in data challenges.
  • Standardized input/output formats and reproducible workflows are essential for reliable tool assessment.
  • Crowd-sourced benchmarking facilitates wider participation and validation of analytical tools.

Outlook:

  • Future biomedical data challenges should integrate advanced virtualization and cloud-based solutions.
  • Developing standardized data formats and reporting guidelines will foster greater data sharing and collaboration.
  • Continued focus on reproducible research methodologies will accelerate scientific discovery in quantitative biomedical analysis.