Scientific article
English

Image-Based Quantitation of Host Cell–Toxoplasma gondii Interplay Using HRMAn : A Host Response to Microbe Analysis Pipeline

Published inMethods in molecular biology, vol. 2071, p. 411-433
Publication date2020
First online date2019-11-23
Abstract

Research on Toxoplasma gondii and its interplay with the host is often performed using fluorescence microscopy-based imaging experiments combined with manual quantification of acquired images. We present here an accurate and unbiased quantification method for host-pathogen interactions. We describe how to plan experiments and prepare, stain and image infected specimens and analyze them with the program HRMAn (Host Response to Microbe Analysis). HRMAn is a high-content image analysis method based on KNIME Analytics Platform. Users of this guide will be able to perform infection studies in high-throughput volume and to a greater level of detail. Relying on cutting edge machine learning algorithms, HRMAn can be trained and tailored to many experimental settings and questions.

Keywords
  • Artificial intelligence
  • HRMAn
  • High-content image analysis
  • Host–pathogen interaction
  • KNIME Analytics platform
  • Machine learning
  • Toxoplasma gondii
UNIGE affiliation entities Not a UNIGE publication
Citation (ISO format)
FISCH, Daniel et al. Image-Based Quantitation of Host Cell–Toxoplasma gondii Interplay Using HRMAn : A Host Response to Microbe Analysis Pipeline. In: Methods in molecular biology, 2020, vol. 2071, p. 411–433. doi: 10.1007/978-1-4939-9857-9_21
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Article (Published version)
accessLevelRestricted
Identifiers
Journal ISSN1064-3745
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