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

You might also read

Related Articles

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

Sort by
Same author

Circulating Neutrophils Exhibit an Altered Immune Response in Chronic LUTS: An Image-Based Deep Learning Analysis.

International urogynecology journal·2026
Same author

DeBCR: a sparsity-efficient framework for image enhancement through a deep-learning-based solution to inverse problems.

Communications engineering·2026
Same author

Regularized Gradient Statistics Improve Generative Deep Learning Models of Super Resolution Microscopy.

Small methods·2025
Same author

A Benchmark for Virus Infection Reporter Virtual Staining in Fluorescence and Brightfield Microscopy.

Scientific data·2025
Same author

A digital photography dataset for Vaccinia Virus plaque quantification using Deep Learning.

Scientific data·2025
Same author

Artificial Intelligence Methods in Infection Biology Research.

Methods in molecular biology (Clifton, N.J.)·2025

Related Experiment Video

Updated: Jan 14, 2026

Viral Concentration Determination Through Plaque Assays: Using Traditional and Novel Overlay Systems
09:28

Viral Concentration Determination Through Plaque Assays: Using Traditional and Novel Overlay Systems

Published on: November 4, 2014

115.9K

PyPlaque is an open-source python package for phenotypic analysis of virus plaque assays.

Trina De1,2, Vardan Andriasyan3,4, Artur Yakimovich5,6,7,8

  • 1Center for Advanced Systems Understanding (CASUS), Görlitz, Germany.

Scientific Reports
|October 16, 2025
PubMed
Summary
This summary is machine-generated.

PyPlaque is a new open-source Python package for quantifying virus particles in plaque assays. It offers a flexible, modular design to improve measurement accuracy and analysis in virology research.

More Related Videos

Plaquing of Herpes Simplex Viruses
04:41

Plaquing of Herpes Simplex Viruses

Published on: November 5, 2021

6.8K
Aseptic Laboratory Techniques: Plating Methods
18:00

Aseptic Laboratory Techniques: Plating Methods

Published on: May 11, 2012

750.9K

Related Experiment Videos

Last Updated: Jan 14, 2026

Viral Concentration Determination Through Plaque Assays: Using Traditional and Novel Overlay Systems
09:28

Viral Concentration Determination Through Plaque Assays: Using Traditional and Novel Overlay Systems

Published on: November 4, 2014

115.9K
Plaquing of Herpes Simplex Viruses
04:41

Plaquing of Herpes Simplex Viruses

Published on: November 5, 2021

6.8K
Aseptic Laboratory Techniques: Plating Methods
18:00

Aseptic Laboratory Techniques: Plating Methods

Published on: May 11, 2012

750.9K

Area of Science:

  • Virology
  • Bioimage Analysis
  • Computational Biology

Background:

  • Virological plaque assays are crucial for quantifying infectious viral particles.
  • Current software for plaque assay image analysis often lacks modularity, exhibits measurement discrepancies, and is closed-source.
  • These limitations present significant hurdles in bioimage analysis for virology.

Purpose of the Study:

  • To introduce PyPlaque, an open-source Python package designed for flexible and modular quantification of virological plaque assays.
  • To address the limitations of existing tools by providing an adaptable solution for image analysis.
  • To improve the accuracy and consistency of plaque count measurements.

Main Methods:

  • Developed PyPlaque as an open-source Python package utilizing object-oriented programming.
  • Implemented an abstracted architecture to accommodate diverse experimental formats and specimen carriers.
  • Focused on phenotype-specific information extraction and analysis at multiple granularity levels.

Main Results:

  • PyPlaque demonstrates enhanced flexibility and modularity compared to existing tools.
  • The package effectively alleviates measurement disagreements in plaque assays.
  • The object-oriented design facilitates adaptation to various experimental containers and biological contexts.

Conclusions:

  • PyPlaque offers a versatile and open-source solution for virological plaque assay quantification.
  • Its modular design and focus on accuracy make it a valuable tool for researchers.
  • The underlying architectural principles are generalizable to other bioimage analysis tasks.