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Cancer Gene Networks

Overview of attention for book
Cover of 'Cancer Gene Networks'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction: Cancer Gene Networks.
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    Chapter 2 Emerging Methods in Chemoproteomics with Relevance to Drug Discovery.
  4. Altmetric Badge
    Chapter 3 ANXA7-GTPase as Tumor Suppressor: Mechanisms and Therapeutic Opportunities.
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    Chapter 4 Experimental and Study Design Considerations for Uncovering Oncometabolites.
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    Chapter 5 Targeting Deubiquitinating Enzymes and Autophagy in Cancer.
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    Chapter 6 Quantitative Clinical Imaging Methods for Monitoring Intratumoral Evolution.
  8. Altmetric Badge
    Chapter 7 Transcriptome and Proteome Analyses of TNFAIP8 Knockdown Cancer Cells Reveal New Insights into Molecular Determinants of Cell Survival and Tumor Progression.
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    Chapter 8 Network-Oriented Approaches to Anticancer Drug Response.
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    Chapter 9 CRISPR/Cas-Mediated Knockin in Human Pluripotent Stem Cells.
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    Chapter 10 Complete Transcriptome RNA-Seq.
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    Chapter 11 Computational Methods and Correlation of Exon-skipping Events with Splicing, Transcription, and Epigenetic Factors.
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    Chapter 12 Tissue Engineering Platforms to Replicate the Tumor Microenvironment of Multiple Myeloma.
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    Chapter 13 microRNA Target Prediction.
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    Chapter 14 Evaluating the Delivery of Proteins to the Cytosol of Mammalian Cells.
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    Chapter 15 Validation of Biomarker Proteins Using Reverse Capture Protein Microarrays.
  17. Altmetric Badge
    Chapter 16 Chemical Synthesis of Activity-Based Diubiquitin Probes.
  18. Altmetric Badge
    Chapter 17 Profiling the Dual Enzymatic Activities of the Serine/Threonine Kinase IRE1α.
Attention for Chapter 10: Complete Transcriptome RNA-Seq.
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

blogs
1 blog

Citations

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1 Dimensions

Readers on

mendeley
24 Mendeley
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Chapter title
Complete Transcriptome RNA-Seq.
Chapter number 10
Book title
Cancer Gene Networks
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6539-7_10
Pubmed ID
Book ISBNs
978-1-4939-6537-3, 978-1-4939-6539-7
Authors

David F. B. Miller, Pearlly Yan, Fang Fang, Aaron Buechlein, Karl Kroll, David Frankhouser, Cameron Stump, Paige Stump, James B. Ford, Haixu Tang, Scott Michaels, Daniela Matei, Tim H. Huang, Jeremy Chien, Yunlong Liu, Douglas B. Rusch, Kenneth P. Nephew

Editors

Usha Kasid, Robert Clarke

Abstract

RNA-Seq is the leading technology for analyzing gene expression on a global scale across a broad spectrum of sample types. However, due to chemical modifications by fixation or degradation due to collection methods, samples often contain an abundance of RNA that is no longer intact, and the capability of current RNA-Seq protocols to accurately quantify such samples is often limited. We have developed an RNA-Seq protocol to address these key issues as well as quantify gene expression from the whole transcriptome. Furthermore, for compatibility with improved sequencing platforms, we use restructured adapter sequences to generate libraries for Illumina HiSeq, MiSeq, and NextSeq platforms. Our protocol utilizes duplex-specific nuclease (DSN) to remove abundant ribosomal RNA sequences while retaining other types of RNA for superior transcriptome profiling from low quantity input. We employ the Illumina sequencing platform, but this method is described in sufficient detail to adapt to other platforms.

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Ph. D. Student 5 21%
Student > Master 3 13%
Student > Doctoral Student 2 8%
Student > Postgraduate 2 8%
Other 4 17%
Unknown 2 8%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 46%
Agricultural and Biological Sciences 6 25%
Medicine and Dentistry 2 8%
Immunology and Microbiology 1 4%
Psychology 1 4%
Other 1 4%
Unknown 2 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 09 November 2016.
All research outputs
#1,688,773
of 8,608,742 outputs
Outputs from Methods in molecular biology
#566
of 6,331 outputs
Outputs of similar age
#66,234
of 245,295 outputs
Outputs of similar age from Methods in molecular biology
#7
of 35 outputs
Altmetric has tracked 8,608,742 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,331 research outputs from this source. They receive a mean Attention Score of 1.9. This one has done particularly well, scoring higher than 90% 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 245,295 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 72% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.