HRMAn

HRMAn performs quantitative high-content image analysis of host–pathogen interactions from immunofluorescent and fluorescence microscopy data, enabling automated measurement and high-throughput analysis with application to Toxoplasma gondii studies.

Key Features:

• High-Content Image Analysis: Implements high-content image analysis methodologies for extraction of quantitative features from microscopy images.
• KNIME Integration: Uses the KNIME Analytics Platform for data processing and workflow construction.
• Machine Learning Integration: Incorporates machine learning algorithms that can be trained and customized for different experimental settings.
• Automated Quantification: Automates quantification of parameters derived from fluorescence microscopy and immunofluorescent imaging experiments.
• High-Throughput Capability: Supports analysis workflows suitable for high-throughput infection studies and large-scale datasets.

Scientific Applications:

• Host–pathogen interaction quantification: Quantifies interactions between host cells and pathogens such as Toxoplasma gondii from microscopy data.
• Immunofluorescent image analysis: Processes and extracts quantitative measurements from immunofluorescently labeled specimens.
• High-throughput infection studies: Enables large-scale analysis of infection experiments to support statistical and comparative studies.
• Experimental workflow support: Supports planning and execution steps that connect specimen preparation, staining, imaging, and downstream image analysis.

Methodology:

High-content image analysis implemented as KNIME workflows with automated quantification of fluorescence microscopy images and machine learning–based components for customizable classification and measurement.