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High Content Screening

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Cover of 'High Content Screening'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Applications and Caveats on the Utilization of DNA-Specific Probes in Cell-Based Assays
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    Chapter 2 General Staining and Segmentation Procedures for High Content Imaging and Analysis
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    Chapter 3 Tools to Measure Cell Health and Cytotoxicity Using High Content Imaging and Analysis
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    Chapter 4 Cell-Based High Content Analysis of Cell Proliferation and Apoptosis
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    Chapter 5 Tools to Measure Autophagy Using High Content Imaging and Analysis
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    Chapter 6 Guidelines for Microplate Selection in High Content Imaging
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    Chapter 7 Quality Control for High-Throughput Imaging Experiments Using Machine Learning in Cellprofiler
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    Chapter 8 High-Content Screening Approaches That Minimize Confounding Factors in RNAi, CRISPR, and Small Molecule Screening
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    Chapter 9 Strategies and Solutions to Maintain and Retain Data from High Content Imaging, Analysis, and Screening Assays
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    Chapter 10 Live-Cell High Content Screening in Drug Development
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    Chapter 11 Challenges and Opportunities in Enabling High-Throughput, Miniaturized High Content Screening
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    Chapter 12 Translocation Biosensors—Versatile Tools to Probe Protein Functions in Living Cells
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    Chapter 13 High Content Positional Biosensor Assay to Screen for Compounds that Prevent or Disrupt Androgen Receptor and Transcription Intermediary Factor 2 Protein-Protein Interactions
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    Chapter 14 High Content Imaging Assays for IL-6-Induced STAT3 Pathway Activation in Head and Neck Cancer Cell Lines
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    Chapter 15 Single Cell and Population Level Analysis of HCA Data
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    Chapter 16 Utilization of Multidimensional Data in the Analysis of Ultra-High-Throughput High Content Phenotypic Screens
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    Chapter 17 High Content Screening of Mammalian Primary Cortical Neurons
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    Chapter 18 Human-Derived Neurons and Neural Progenitor Cells in High Content Imaging Applications
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    Chapter 19 Determination of Hepatotoxicity in iPSC-Derived Hepatocytes by Multiplexed High Content Assays
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    Chapter 20 The Generation of Three-Dimensional Head and Neck Cancer Models for Drug Discovery in 384-Well Ultra-Low Attachment Microplates
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    Chapter 21 An Endothelial Cell/Mesenchymal Stem Cell Coculture Cord Formation Assay to Model Vascular Biology In Vitro
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    Chapter 22 High-Throughput Automated Chemical Screens in Zebrafish
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    Chapter 23 Erratum to: High Content Screening
Attention for Chapter 11: Challenges and Opportunities in Enabling High-Throughput, Miniaturized High Content Screening
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Chapter title
Challenges and Opportunities in Enabling High-Throughput, Miniaturized High Content Screening
Chapter number 11
Book title
High Content Screening
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7357-6_11
Pubmed ID
Book ISBNs
978-1-4939-7355-2, 978-1-4939-7357-6
Authors

Debra Nickischer, Lisa Elkin, Normand Cloutier, Jonathan O’Connell, Martyn Banks, Andrea Weston

Abstract

Within the Drug Discovery industry, there is a growing recognition of the value of high content screening (HCS), particularly as researchers aim to screen compounds and identify hits using more physiologically relevant in vitro cell-based assays. Image-based high content screening, with its combined ability to yield multiparametric data, provide subcellular resolution, and enable cell population analysis, is well suited to this challenge. While HCS has been in routine use for over a decade, a number of hurdles have historically prohibited very large, miniaturized high-throughput screening efforts with this platform. Suitable hardware and consumables for conducting 1536-well HCS have only recently become available, and developing a reliable informatics framework to accommodate the scale of high-throughput HCS data remains a considerable challenge. Additionally, innovative approaches are needed to interpret the large volumes of content-rich information generated. Despite these hurdles, there has been a growing interest in screening large compound inventories using this platform. Here, we outline the infrastructure developed and applied at Bristol-Myers Squibb for 1536-well high content screening and discuss key lessons learned.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 25%
Student > Ph. D. Student 3 19%
Lecturer 2 13%
Student > Master 2 13%
Professor 1 6%
Other 1 6%
Unknown 3 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 13%
Biochemistry, Genetics and Molecular Biology 2 13%
Chemistry 2 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Business, Management and Accounting 1 6%
Other 4 25%
Unknown 4 25%