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Cancer Gene Profiling

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

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Factors Affecting the Use of Human Tissues in Biomedical Research: Implications in the Design and Operation of a Biorepository.
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    Chapter 2 Tissue Microdissection.
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    Chapter 3 Tissue Microarrays.
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    Chapter 4 Gene Expression Analysis in the Age of Mass Sequencing: An Introduction.
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    Chapter 5 Quantitative DNA Methylation Profiling in Cancer.
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    Chapter 6 Cancer Gene Profiling
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    Chapter 7 Exosomes in Cancer Disease.
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    Chapter 8 MicroRNA (miRNA) Profiling.
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    Chapter 9 Cancer Gene Profiling for Response Prediction.
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    Chapter 10 Target Gene Discovery for Novel Therapeutic Agents in Cancer Treatment.
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    Chapter 11 Application of Proteomics in Cancer Biomarker Discovery: GeLC-MS/MS
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    Chapter 12 Meta-analysis of Cancer Gene Profiling Data.
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    Chapter 13 Reproducible, Scalable Fusion Gene Detection from RNA-Seq.
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    Chapter 14 Transcriptome Sequencing for the Detection of Chimeric Transcripts.
Attention for Chapter 8: MicroRNA (miRNA) Profiling.
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Citations

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Chapter title
MicroRNA (miRNA) Profiling.
Chapter number 8
Book title
Cancer Gene Profiling
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3204-7_8
Pubmed ID
26667459
Book ISBNs
978-1-4939-3203-0, 978-1-4939-3204-7
Authors

Gao, Lu, Jiang, Feng, Lu Gao, Feng Jiang

Editors

Robert Grützmann, Christian Pilarsky

Abstract

MicroRNAs (miRNAs) are small, highly conserved noncoding RNA molecules involved in the regulation of gene expression. Since each miRNA regulates the expression of hundreds of target mRNAs, miRNAs could function as master coordinators, efficiently regulating fundamental cellular processes, including proliferation, apoptosis, and development. Furthermore, miRNAs may provide useful diagnostic and therapeutic targets in a variety of diseases. However, miRNA expression profiling is essential for the investigation of the biological functions and clinical applications of miRNAs. Therefore, in this chapter, we review and discuss commonly used techniques for miRNAs profiling, as well as their advantages and restrictions.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Ireland 1 3%
Unknown 31 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 18%
Student > Master 5 15%
Student > Ph. D. Student 4 12%
Lecturer 3 9%
Student > Bachelor 3 9%
Other 6 18%
Unknown 6 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 30%
Medicine and Dentistry 6 18%
Agricultural and Biological Sciences 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Computer Science 1 3%
Other 5 15%
Unknown 7 21%
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 04 February 2016.
All research outputs
#17,778,896
of 22,835,198 outputs
Outputs from Methods in molecular biology
#7,239
of 13,126 outputs
Outputs of similar age
#267,677
of 393,568 outputs
Outputs of similar age from Methods in molecular biology
#752
of 1,470 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% 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 is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 393,568 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
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 is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.

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