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High-Throughput Screening Assays in Toxicology

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Cover of 'High-Throughput Screening Assays in Toxicology'

Table of Contents

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    Book Overview
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    Chapter 1 Monitoring Ligand-Activated Protein–Protein Interactions Using Bioluminescent Resonance Energy Transfer (BRET) Assay
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    Chapter 2 Mitochondrial Membrane Potential Assay
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    Chapter 3 High-Throughput Screening Assays in Toxicology
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    Chapter 4 Quantitative High-Throughput Luciferase Screening in Identifying CAR Modulators
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    Chapter 5 Transactivation and Coactivator Recruitment Assays for Measuring Farnesoid X Receptor Activity
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    Chapter 6 Cell-Based Assay for Identifying the Modulators of Antioxidant Response Element Signaling Pathway
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    Chapter 7 Study Liver Cytochrome P450 3A4 Inhibition and Hepatotoxicity Using DMSO-Differentiated HuH-7 Cells
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    Chapter 8 Determination of Histone H2AX Phosphorylation in DT40 Cells
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    Chapter 9 High-Throughput and High-Content Micronucleus Assay in CHO-K1 Cells
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    Chapter 10 High-Throughput Screening Assays in Toxicology
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    Chapter 11 High-Throughput Screening Assays in Toxicology
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    Chapter 12 A Quantitative High-Throughput Screening Data Analysis Pipeline for Activity Profiling
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    Chapter 13 Correction of Microplate Data from High-Throughput Screening
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    Chapter 14 CurveP Method for Rendering High-Throughput Screening Dose-Response Data into Digital Fingerprints
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    Chapter 15 Accounting Artifacts in High-Throughput Toxicity Assays
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    Chapter 16 Accessing the High-Throughput Screening Data Landscape
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    Chapter 17 Curating and Preparing High-Throughput Screening Data for Quantitative Structure-Activity Relationship Modeling
Attention for Chapter 15: Accounting Artifacts in High-Throughput Toxicity Assays
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Chapter title
Accounting Artifacts in High-Throughput Toxicity Assays
Chapter number 15
Book title
High-Throughput Screening Assays in Toxicology
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-6346-1_15
Pubmed ID
Book ISBNs
978-1-4939-6344-7, 978-1-4939-6346-1
Authors

Jui-Hua Hsieh, Hsieh, Jui-Hua

Abstract

Compound activity identification is the primary goal in high-throughput screening (HTS) assays. However, assay artifacts including both systematic (e.g., compound auto-fluorescence) and nonsystematic (e.g., noise) complicate activity interpretation. In addition, other than the traditional potency parameter, half-maximal effect concentration (EC50), additional activity parameters (e.g., point-of-departure, POD) could be derived from HTS data for activity profiling. A data analysis pipeline has been developed to handle the artifacts and to provide compound activity characterization with either binary or continuous metrics. This chapter outlines the steps in the pipeline using Tox21 glucocorticoid receptor (GR) β-lactamase assays, including the formats to identify either agonists or antagonists, as well as the counter-screen assays for identifying artifacts as examples. The steps can be applied to other lower-throughput assays with concentration-response data.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 67%
Student > Postgraduate 1 33%
Readers by discipline Count As %
Environmental Science 1 33%
Biochemistry, Genetics and Molecular Biology 1 33%
Agricultural and Biological Sciences 1 33%