↓ Skip to main content

High Content Screening

Overview of attention for book
Cover of 'High Content Screening'

Table of Contents

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

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
6 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
High-Content Screening Approaches That Minimize Confounding Factors in RNAi, CRISPR, and Small Molecule Screening
Chapter number 8
Book title
High Content Screening
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7357-6_8
Pubmed ID
Book ISBNs
978-1-4939-7355-2, 978-1-4939-7357-6
Authors

Steven A. Haney

Abstract

Screening arrayed libraries of reagents, particularly small molecules began as a vehicle for drug discovery, but the in last few years it has become a cornerstone of biological investigation, joining RNAi and CRISPR as methods for elucidating functional relationships that could not be anticipated, and illustrating the mechanisms behind basic and disease biology, and therapeutic resistance. However, these approaches share some common challenges, especially with respect to specificity or selectivity of the reagents as they are scaled to large protein families or the genome. High-content screening (HCS) has emerged as an important complement to screening, mostly the result of a wide array of specific molecular events, such as protein kinase and transcription factor activation, morphological changes associated with stem cell differentiation or the epithelial-mesenchymal transition of cancer cells. Beyond the range of cellular events that can be screened by HCS, image-based screening introduces new processes for differentiating between specific and nonspecific effects on cells. This chapter introduces these complexities and discusses strategies available in image-based screening that can mitigate the challenges they can bring to screening.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 33%
Student > Doctoral Student 1 17%
Other 1 17%
Student > Master 1 17%
Student > Ph. D. Student 1 17%
Other 0 0%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 50%
Agricultural and Biological Sciences 1 17%
Immunology and Microbiology 1 17%
Medicine and Dentistry 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 November 2017.
All research outputs
#16,592,728
of 25,200,621 outputs
Outputs from Methods in molecular biology
#5,278
of 14,137 outputs
Outputs of similar age
#270,510
of 455,374 outputs
Outputs of similar age from Methods in molecular biology
#509
of 1,486 outputs
Altmetric has tracked 25,200,621 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,137 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 58% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 455,374 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,486 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.