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LiveCellMiner: A new tool to analyze mitotic progression.

Daniel Moreno-Andrés1, Anuk Bhattacharyya2, Anja Scheufen1

  • 1Institute of Biochemistry and Molecular Cell Biology, Medical School, RWTH Aachen University, Aachen, Germany.

Plos One
|July 7, 2022
PubMed
Summary

LiveCellMiner is a new open-source software tool for analyzing live-cell imaging data. It automates the extraction and visualization of cell cycle and mitotic features, overcoming limitations of current methods.

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Last Updated: Sep 5, 2025

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Area of Science:

  • Cell Biology
  • Microscopy
  • Bioinformatics

Background:

  • Live-cell imaging is crucial for studying cell cycle and mitotic defects, generating large datasets.
  • Existing automated image analysis tools lack flexibility and require experiment-specific training data, hindering full automation.

Purpose of the Study:

  • To introduce LiveCellMiner, a flexible open-source software for automated analysis of live-cell imaging data.
  • To enable quantitative and unbiased analysis of high-content screening datasets across different platforms.

Main Methods:

  • Development of LiveCellMiner, a software tool for automated extraction, analysis, and visualization of image features.
  • Application to analyze dynamic chromatin and tubulin cytoskeleton features in human cells during mitosis.

Main Results:

  • LiveCellMiner provides automated, quantitative, and unbiased analysis of aggregated and time-resolved image features.
  • Demonstrated versatility in analyzing mitotic and cell cycle dynamics across diverse experimental setups.

Conclusions:

  • LiveCellMiner offers a flexible and versatile solution for automating live-cell imaging data analysis.
  • The tool addresses key bottlenecks in high-content screening, facilitating broader research applications.