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Disease Gene Identification

Overview of attention for book
Cover of 'Disease Gene Identification'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Identification of Disease Susceptibility Alleles in the Next Generation Sequencing Era
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    Chapter 2 Induced Pluripotent Stem Cells in Disease Modeling and Gene Identification
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    Chapter 3 Development of Targeted Therapies Based on Gene Modification
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    Chapter 4 What Can We Learn About Human Disease from the Nematode C. elegans?
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    Chapter 5 Microbiome Sequencing Methods for Studying Human Diseases
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    Chapter 6 The Emerging Role of Long Noncoding RNAs in Human Disease
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    Chapter 7 Identification of Disease-Related Genes Using a Genome-Wide Association Study Approach
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    Chapter 8 Whole Genome Library Construction for Next Generation Sequencing
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    Chapter 9 Whole Exome Library Construction for Next Generation Sequencing
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    Chapter 10 Optimized Methodology for the Generation of RNA-Sequencing Libraries from Low-Input Starting Material: Enabling Analysis of Specialized Cell Types and Clinical Samples
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    Chapter 11 Using Fluidigm C1 to Generate Single-Cell Full-Length cDNA Libraries for mRNA Sequencing
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    Chapter 12 MiSeq: A Next Generation Sequencing Platform for Genomic Analysis
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    Chapter 13 Methods for CpG Methylation Array Profiling Via Bisulfite Conversion
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    Chapter 14 miRNA Quantification Method Using Quantitative Polymerase Chain Reaction in Conjunction with C q Method
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    Chapter 15 Primary Airway Epithelial Cell Gene Editing Using CRISPR-Cas9
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    Chapter 16 RNA Interference to Knock Down Gene Expression
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    Chapter 17 Using Luciferase Reporter Assays to Identify Functional Variants at Disease-Associated Loci
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    Chapter 18 Physiologic Interpretation of GWAS Signals for Type 2 Diabetes
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    Chapter 19 Identification of Genes for Hereditary Hemochromatosis
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    Chapter 20 Identification of Driver Mutations in Rare Cancers: The Role of SMARCA4 in Small Cell Carcinoma of the Ovary, Hypercalcemic Type (SCCOHT)
  22. Altmetric Badge
    Chapter 21 The Rise and Fall and Rise of Linkage Analysis as a Technique for Finding and Characterizing Inherited Influences on Disease Expression
Attention for Chapter 6: The Emerging Role of Long Noncoding RNAs in Human Disease
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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 (79th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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Chapter title
The Emerging Role of Long Noncoding RNAs in Human Disease
Chapter number 6
Book title
Disease Gene Identification
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7471-9_6
Pubmed ID
Book ISBNs
978-1-4939-7470-2, 978-1-4939-7471-9
Authors

Johanna K. DiStefano, DiStefano, Johanna K.

Abstract

Only a small fraction of the human genome corresponds to protein-coding genes. Historically, the vast majority of genomic sequence was dismissed as transcriptionally silent, but recent large-scale investigations have instead revealed a rich array of functionally significant elements, including non-protein-coding transcripts, within the noncoding regions of the human genome. Long noncoding RNAs (lncRNAs), a class of noncoding transcripts with lengths >200 nucleotides, are pervasively transcribed in the genome, and have been shown to bind DNA, RNA, and protein. LncRNAs exert effects through a variety of mechanisms that include guiding chromatin-modifying complexes to specific genomic loci, providing molecular scaffolds, modulating transcriptional programs, and regulating miRNA expression. An increasing number of experimental studies are providing evidence that lncRNAs mediate disease pathogenesis, thereby challenging the concept that protein-coding genes are the sole contributors to the development of human disease. This chapter highlights recent findings linking lncRNAs with human diseases of complex etiology, including hepatocellular carcinoma, Alzheimer's disease, and diabetes.

X Demographics

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 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 107 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 20%
Student > Master 17 16%
Student > Bachelor 17 16%
Researcher 12 11%
Student > Postgraduate 6 6%
Other 9 8%
Unknown 25 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 46 43%
Agricultural and Biological Sciences 11 10%
Medicine and Dentistry 7 7%
Neuroscience 4 4%
Immunology and Microbiology 3 3%
Other 9 8%
Unknown 27 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 27 May 2019.
All research outputs
#4,684,286
of 25,301,208 outputs
Outputs from Methods in molecular biology
#1,217
of 14,173 outputs
Outputs of similar age
#94,015
of 456,093 outputs
Outputs of similar age from Methods in molecular biology
#92
of 1,486 outputs
Altmetric has tracked 25,301,208 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,173 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 91% 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 456,093 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 1,486 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.