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Microarray Technology

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Cover of 'Microarray Technology'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Overview of Microarray Technology.
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    Chapter 2 Surface Functionalization for Immobilization of Probes on Microarrays.
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    Chapter 3 The "Clickable" Method for Oligonucleotide Immobilization Onto Azide-Functionalized Microarrays.
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    Chapter 4 Microarray Developed on Plastic Substrates.
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    Chapter 5 Detection and Quantification of MicroRNAs by Ligase-Assisted Sandwich Hybridization on a Microarray.
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    Chapter 6 Probe Design Strategies for Oligonucleotide Microarrays.
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    Chapter 7 Analyzing Illumina Gene Expression Microarray Data Obtained From Human Whole Blood Cell and Blood Monocyte Samples
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    Chapter 8 Microarray Technology and Its Applications for Detecting Plasma microRNA Biomarkers in Digestive Tract Cancers.
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    Chapter 9 Microarray Technology
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    Chapter 10 High-Throughput DNA Array for SNP Detection of KRAS Gene Using a Centrifugal Microfluidic Device.
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    Chapter 11 Single Nucleotide Polymorphisms as Genomic Markers for High-Throughput Pharmacogenomic Studies.
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    Chapter 12 DNA Microarray-Based Diagnostics.
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    Chapter 13 Microarray Technology
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    Chapter 14 Nanotechnology in the Fabrication of Protein Microarrays
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    Chapter 15 Epitope Mapping Using Peptide Microarray in Autoantibody Profiling
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    Chapter 16 Preparation of Glycan Arrays Using Pyridylaminated Glycans
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    Chapter 17 Competitive Immunoassays Using Antigen Microarrays
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    Chapter 18 Parallel Syntheses of Peptides on Teflon-Patterned Paper Arrays (SyntArrays).
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    Chapter 19 Cell Microarrays for Biomedical Applications.
Attention for Chapter 6: Probe Design Strategies for Oligonucleotide Microarrays.
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Chapter title
Probe Design Strategies for Oligonucleotide Microarrays.
Chapter number 6
Book title
Microarray Technology
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3136-1_6
Pubmed ID
Book ISBNs
978-1-4939-3135-4, 978-1-4939-3136-1
Authors

Parisot, Nicolas, Peyretaillade, Eric, Dugat-Bony, Eric, Denonfoux, Jérémie, Mahul, Antoine, Peyret, Pierre, Nicolas Parisot, Eric Peyretaillade, Eric Dugat-Bony, Jérémie Denonfoux, Antoine Mahul, Pierre Peyret

Abstract

Oligonucleotide microarrays have been widely used for gene detection and/or quantification of gene expression in various samples ranging from a single organism to a complex microbial assemblage. The success of a microarray experiment, however, strongly relies on the quality of designed probes. Consequently, probe design is of critical importance and therefore multiple parameters should be considered for each probe in order to ensure high specificity, sensitivity, and uniformity as well as potentially quantitative power. Moreover, to assess the complete gene repertoire of complex biological samples such as those studied in the field of microbial ecology, exploratory probe design strategies must be also implemented to target not-yet-described sequences. To design such probes, two algorithms, KASpOD and HiSpOD, have been developed and they are available via two user-friendly web services. Here, we describe the use of this software necessary for the design of highly effective probes especially in the context of microbial oligonucleotide microarrays by taking into account all the crucial parameters.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Student > Master 7 19%
Researcher 6 16%
Student > Doctoral Student 2 5%
Student > Postgraduate 2 5%
Other 5 14%
Unknown 6 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 22%
Chemistry 5 14%
Agricultural and Biological Sciences 5 14%
Engineering 4 11%
Immunology and Microbiology 2 5%
Other 5 14%
Unknown 8 22%
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 08 September 2016.
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#20,297,343
of 22,834,308 outputs
Outputs from Methods in molecular biology
#9,916
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#330,625
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Outputs of similar age from Methods in molecular biology
#1,053
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