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Related Concept Videos

Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Related Experiment Video

Updated: Jun 19, 2026

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
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CellProfiler plugins - An easy image analysis platform integration for containers and Python tools.

Erin Weisbart1, Callum Tromans-Coia1, Barbara Diaz-Rohrer1

  • 1Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

Journal of Microscopy
|September 10, 2023
PubMed
Summary
This summary is machine-generated.

CellProfiler plugins enhance image analysis workflows with new modules and containerized tools. This upgraded repository improves usability and community contributions for reproducible scientific imaging.

Keywords:
CellProfilerPythonimage analysispluginsoftwaresoftware containerworkflow

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Area of Science:

  • Bioimage analysis
  • Computational biology
  • Scientific software development

Background:

  • CellProfiler is a popular open-source software for reproducible biological image analysis.
  • Its plugin system enables integration with external Python tools and containerized applications.
  • The CellProfiler-plugins repository hosts experimental and dependency-heavy modules.

Purpose of the Study:

  • To present an upgraded CellProfiler-plugins repository.
  • To demonstrate accessing containerized tools within CellProfiler.
  • To improve documentation and add citation/reference functionalities.

Main Methods:

  • Developed and integrated new modules into the CellProfiler-plugins repository.
  • Implemented examples for accessing containerized tools.
  • Enhanced existing documentation and added citation management features.

Main Results:

  • An upgraded CellProfiler-plugins repository is now available.
  • Users can access containerized tools for expanded image analysis capabilities.
  • Improved documentation and citation tools facilitate easier use and contribution.

Conclusions:

  • The enhanced CellProfiler-plugins repository lowers barriers for advanced image analysis.
  • It promotes reproducibility and community engagement in scientific software.
  • Facilitates integration of diverse computational tools into bioimage analysis workflows.