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

Daniel Fisch, Artur Yakimovich, Barbara Clough, Jason Mercer, Eva Maria Frickel

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
EditorsChristopher J Tonkin
PublisherHumana Press
Pages411-433
Number of pages23
Volume2071
ISBN (Electronic)9781493998579
ISBN (Print)9781493998562
DOIs
Publication statusPublished - 23 Nov 2019

Publication series

NameMethods in Molecular Biology
Volume2071
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Artificial intelligence
  • High-content image analysis
  • Host–pathogen interaction
  • HRMAn
  • KNIME Analytics platform
  • Machine learning
  • Toxoplasma gondii

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

Fingerprint

Dive into the research topics of 'Image-Based Quantitation of Host Cell–Toxoplasma gondii Interplay Using HRMAn: A Host Response to Microbe Analysis Pipeline'. Together they form a unique fingerprint.

Cite this