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Yeast Functional Genomics

Overview of attention for book
Cover of 'Yeast Functional Genomics'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Using RNA-seq for Analysis of Differential Gene Expression in Fungal Species.
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    Chapter 2 Enhancing Structural Annotation of Yeast Genomes with RNA-Seq Data.
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    Chapter 3 Pathogen Gene Expression Profiling During Infection Using a Nanostring nCounter Platform.
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    Chapter 4 Comparative Transcriptomics in Yeasts.
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    Chapter 5 Mapping the Transcriptome-Wide Landscape of RBP Binding Sites Using gPAR-CLIP-seq: Experimental Procedures.
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    Chapter 6 Mapping the Transcriptome-Wide Landscape of RBP Binding Sites Using gPAR-CLIP-seq: Bioinformatic Analysis.
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    Chapter 7 Translation Analysis at the Genome Scale by Ribosome Profiling.
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    Chapter 8 Biotin-Genomic Run-On (Bio-GRO): A High-Resolution Method for the Analysis of Nascent Transcription in Yeast.
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    Chapter 9 Genome-Wide Probing of RNA Structures In Vitro Using Nucleases and Deep Sequencing.
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    Chapter 10 Genome-Wide Chromatin Immunoprecipitation in Candida albicans and Other Yeasts.
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    Chapter 11 ChIPseq in Yeast Species: From Chromatin Immunoprecipitation to High-Throughput Sequencing and Bioinformatics Data Analyses.
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    Chapter 12 Systematic Determination of Transcription Factor DNA-Binding Specificities in Yeast.
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    Chapter 13 Generation and Analysis of Chromosomal Contact Maps of Yeast Species.
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    Chapter 14 A Versatile Procedure to Generate Genome-Wide Spatiotemporal Program of Replication in Yeast Species.
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    Chapter 15 Single-Step Affinity Purification (ssAP) and Mass Spectrometry of Macromolecular Complexes in the Yeast S. cerevisiae.
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    Chapter 16 Label-Free Quantitative Proteomics in Yeast.
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    Chapter 17 Profiling of Yeast Lipids by Shotgun Lipidomics.
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    Chapter 18 Identification of Links Between Cellular Pathways by Genetic Interaction Mapping (GIM).
  20. Altmetric Badge
    Chapter 19 On the Mapping of Epistatic Genetic Interactions in Natural Isolates: Combining Classical Genetics and Genomics.
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    Chapter 20 Experimental Evolution and Resequencing Analysis of Yeast.
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    Chapter 21 Reconstruction and Analysis of the Evolution of Modular Transcriptional Regulatory Programs Using Arboretum.
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    Chapter 22 Predicting Gene and Genomic Regulation in Saccharomyces cerevisiae, using the YEASTRACT Database: A Step-by-Step Guided Analysis.
Attention for Chapter 11: ChIPseq in Yeast Species: From Chromatin Immunoprecipitation to High-Throughput Sequencing and Bioinformatics Data Analyses.
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Chapter title
ChIPseq in Yeast Species: From Chromatin Immunoprecipitation to High-Throughput Sequencing and Bioinformatics Data Analyses.
Chapter number 11
Book title
Yeast Functional Genomics
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3079-1_11
Pubmed ID
Book ISBNs
978-1-4939-3078-4, 978-1-4939-3079-1
Authors

Lelandais, Gaëlle, Blugeon, Corinne, Merhej, Jawad, Gaëlle Lelandais, Corinne Blugeon, Jawad Merhej

Abstract

Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIPseq) is a powerful technique for the genome-wide location of protein DNA-binding sites. The ChIP experiment consists in treating living cells with a cross-linking agent to bind proteins to their DNA substrates. After fragmentation of DNA, specific fractions associated with a particular protein of interest are purified by immunoaffinity. They are next sequenced and identified on the reference genome using dedicated bioinformatics programs. Several technical aspects are important to obtain high-quality ChIPseq results. This includes the quality of antibodies, the sequencing protocols, the use of accurate controls and the careful choice of bioinformatics tools. We present here a general protocol to perform ChIPseq analyses in yeast species. This protocol has been optimized to identify target genes of specific transcription factors but can be used for any other DNA binding proteins.

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X Demographics

The data shown below were collected from the profiles of 4 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 29%
Researcher 5 24%
Student > Doctoral Student 2 10%
Student > Master 2 10%
Student > Bachelor 1 5%
Other 2 10%
Unknown 3 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 43%
Biochemistry, Genetics and Molecular Biology 7 33%
Unspecified 1 5%
Unknown 4 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 21 February 2016.
All research outputs
#12,937,813
of 22,830,751 outputs
Outputs from Methods in molecular biology
#3,291
of 13,126 outputs
Outputs of similar age
#179,318
of 393,554 outputs
Outputs of similar age from Methods in molecular biology
#310
of 1,470 outputs
Altmetric has tracked 22,830,751 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,126 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 74% 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 393,554 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.