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Tiling Arrays

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Cover of 'Tiling Arrays'

Table of Contents

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    Book Overview
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    Chapter 1 A Brief Introduction to Tiling Microarrays: Principles, Concepts, and Applications
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    Chapter 2 Design of Tiling Arrays and Their Application to Bacterial Transcriptome Analysis
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    Chapter 3 Transcript Profiling in Arabidopsis with Genome Tiling Microarrays
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    Chapter 4 Genome-Wide Analysis of Transcription Factor-Binding Sites in Skeletal Muscle Cells Using ChIP-Seq.
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    Chapter 5 Analysis of Allele-Specific Gene Expression Using a Target-Oriented Tiling Microarray Assay
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    Chapter 6 Detection of Epigenetic Alterations Using Tiling Arrays
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    Chapter 7 Investigating Gene Promoter Methylation in a Mouse Model of Status Epilepticus
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    Chapter 8 Integrative Analysis of ChIP-Chip and ChIP-Seq Dataset
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    Chapter 9 HAT: A Novel Statistical Approach to Discover Functional Regions in the Genome
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    Chapter 10 Inference of Alternative Splicing from Tiling Array Data
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    Chapter 11 Analysis of In Vivo Occupancy of Aebp1, a Transcription Factor, Using High Resolution Tiling Array
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    Chapter 12 Application of the Simple and Efficient Mpeak Modeling in Binding Peak Identification in ChIP-Chip Studies
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    Chapter 13 Evaluation of MeDIP-chip in the context of whole-genome bisulfite sequencing (WGBS-seq) in Arabidopsis. - PubMed - NCBI
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    Chapter 14 Mapping Genomic Features of Tiling Microarray Data by TileMapper
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Title
Tiling Arrays
Published by
Humana Press, August 2013
DOI 10.1007/978-1-62703-607-8
ISBNs
978-1-62703-606-1, 978-1-62703-607-8
Editors

Lee, Tin-Lap, Shui Luk, Alfred Chun

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 3%
China 1 3%
Norway 1 3%
Unknown 30 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 45%
Researcher 9 27%
Student > Bachelor 1 3%
Student > Master 1 3%
Professor > Associate Professor 1 3%
Other 0 0%
Unknown 6 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 48%
Biochemistry, Genetics and Molecular Biology 7 21%
Computer Science 1 3%
Physics and Astronomy 1 3%
Medicine and Dentistry 1 3%
Other 0 0%
Unknown 7 21%