LiveCellMiner

LiveCellMiner provides automated extraction, analysis, and visualization of image features from live-cell imaging datasets as an extension to the SciXMiner MATLAB toolbox to quantify chromatin decondensation and other cellular dynamics.

Key Features:

• Flexibility Across Platforms: Handles high-content data sets obtained from various microscopy platforms.
• Automated Feature Extraction: Automates extraction and analysis of aggregated and time-resolved image features to process large volumes typical of high-throughput microscopy.
• Quantitative and Unbiased Analysis: Employs advanced algorithms to provide quantitative insights into cellular processes while minimizing bias.
• Chromatin and Cytoskeleton Dynamics: Quantifies chromatin decondensation and dynamic tubulin cytoskeleton features during mitosis in human cells.
• Reduced Dependence on Experiment-Specific Inputs: Eliminates the need for dedicated experiment-specific user-annotated training sets and user-defined segmentation parameters.
• Integration with SciXMiner: Functions as an extension to the SciXMiner MATLAB toolbox for image-feature analysis.

Scientific Applications:

• Mitotic and Cell Cycle Defect Analysis: Enables detailed analysis of cellular dynamics relevant to mitotic and cell cycle defects.
• Chromatin Decondensation Quantification: Measures and analyzes chromatin decondensation dynamics in live cells.
• Tubulin Cytoskeleton Investigation: Characterizes dynamic tubulin cytoskeleton features during mitosis in human cells.
• High-Throughput Live-Cell Studies: Supports large-scale live-cell imaging experiments across different experimental and pathological conditions.

Methodology:

Implements automated extraction, analysis, and visualization of aggregated and time-resolved image features within the SciXMiner MATLAB toolbox, employing advanced algorithms and avoiding experiment-specific user-annotated training sets and user-defined segmentation parameters.