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Microarray Methods for Drug Discovery

Overview of attention for book
Cover of 'Microarray Methods for Drug Discovery'

Table of Contents

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    Book Overview
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    Chapter 1 Multicenter Clinical Sample Collection for Microarray Analysis
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    Chapter 2 Isolation of Total RNA from Transgenic Mouse Melanoma Subsets Using Fluorescence-Activated Cell Sorting
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    Chapter 3 Microarray Analysis of Embryonic Stem Cells and Differentiated Embryoid Bodies
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    Chapter 4 Determination of alternate splicing events using the Affymetrix Exon 1.0 ST arrays.
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    Chapter 5 Profiling microRNA Expression with the Illumina BeadChip Platform
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    Chapter 6 TaqMan® Array Cards in Pharmaceutical Research
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    Chapter 7 DMET™ Microarray Technology for Pharmacogenomics-Based Personalized Medicine
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    Chapter 8 The Use of Microarray Technology for Cytogenetics
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    Chapter 9 PCR/LDR/Universal Array Platforms for the Diagnosis of Infectious Disease
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    Chapter 10 RIP-CHIP in Drug Development
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    Chapter 11 ChIPing Away at Global Transcriptional Regulation
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    Chapter 12 HELP (HpaII Tiny Fragment Enrichment by Ligation-Mediated PCR) Assay for DNA Methylation Profiling of Primary Normal and Malignant B Lymphocytes
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    Chapter 13 High-Throughput Screening of Metalloproteases Using Small Molecule Microarrays
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    Chapter 14 Metabolic enzyme microarray coupled with miniaturized cell-culture array technology for high-throughput toxicity screening.
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    Chapter 15 Use of Tissue Microarray to Facilitate Oncology Research
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    Chapter 16 Small Molecule Selectivity and Specificity Profiling Using Functional Protein Microarrays
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    Chapter 17 Production and Application of Glycan Microarrays
Attention for Chapter 14: Metabolic enzyme microarray coupled with miniaturized cell-culture array technology for high-throughput toxicity screening.
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Chapter title
Metabolic enzyme microarray coupled with miniaturized cell-culture array technology for high-throughput toxicity screening.
Chapter number 14
Book title
Microarray Methods for Drug Discovery
Published in
Methods in molecular biology, March 2010
DOI 10.1007/978-1-60761-663-4_14
Pubmed ID
Book ISBNs
978-1-60761-662-7, 978-1-60761-663-4
Authors

Lee MY, Dordick JS, Clark DS, Moo-Yeal Lee, Jonathan S. Dordick, Douglas S. Clark, Lee, Moo-Yeal, Dordick, Jonathan S., Clark, Douglas S.

Abstract

Due to poor drug candidate safety profiles that are often identified late in the drug development process, the clinical progression of new chemical entities to pharmaceuticals remains hindered, thus resulting in the high cost of drug discovery. To accelerate the identification of safer drug candidates and improve the clinical progression of drug candidates to pharmaceuticals, it is important to develop high-throughput tools that can provide early-stage predictive toxicology data. In particular, in vitro cell-based systems that can accurately mimic the human in vivo response and predict the impact of drug candidates on human toxicology are needed to accelerate the assessment of drug candidate toxicity and human metabolism earlier in the drug development process. The in vitro techniques that provide a high degree of human toxicity prediction will be perhaps more important in cosmetic and chemical industries in Europe, as animal toxicity testing is being phased out entirely in the immediate future.We have developed a metabolic enzyme microarray (the Metabolizing Enzyme Toxicology Assay Chip, or MetaChip) and a miniaturized three-dimensional (3D) cell-culture array (the Data Analysis Toxicology Assay Chip, or DataChip) for high-throughput toxicity screening of target compounds and their metabolic enzyme-generated products. The human or rat MetaChip contains an array of encapsulated metabolic enzymes that is designed to emulate the metabolic reactions in the human or rat liver. The human or rat DataChip contains an array of 3D human or rat cells encapsulated in alginate gels for cell-based toxicity screening. By combining the DataChip with the complementary MetaChip, in vitro toxicity results are obtained that correlate well with in vivo rat data.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 20%
Professor 3 15%
Student > Ph. D. Student 3 15%
Student > Doctoral Student 2 10%
Professor > Associate Professor 2 10%
Other 3 15%
Unknown 3 15%
Readers by discipline Count As %
Engineering 5 25%
Biochemistry, Genetics and Molecular Biology 2 10%
Agricultural and Biological Sciences 2 10%
Medicine and Dentistry 2 10%
Chemistry 2 10%
Other 3 15%
Unknown 4 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 12 December 2012.
All research outputs
#18,304,874
of 22,663,150 outputs
Outputs from Methods in molecular biology
#7,811
of 13,021 outputs
Outputs of similar age
#84,732
of 93,735 outputs
Outputs of similar age from Methods in molecular biology
#16
of 21 outputs
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