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Bioinformatics in MicroRNA Research

Overview of attention for book
Cover of 'Bioinformatics in MicroRNA Research'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 MicroRNAs, Long Noncoding RNAs, and Their Functions in Human Disease
  3. Altmetric Badge
    Chapter 2 MicroRNA Expression: Protein Participants in MicroRNA Regulation
  4. Altmetric Badge
    Chapter 3 Viral MicroRNAs, Host MicroRNAs Regulating Viruses, and Bacterial MicroRNA-Like RNAs
  5. Altmetric Badge
    Chapter 4 MicroRNAs: Biomarkers, Diagnostics, and Therapeutics
  6. Altmetric Badge
    Chapter 5 Relational Databases and Biomedical Big Data
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    Chapter 6 Semantic Technologies and Bio-Ontologies
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    Chapter 7 Genome-Wide Analysis of MicroRNA-Regulated Transcripts
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    Chapter 8 Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources
  10. Altmetric Badge
    Chapter 9 Exploring MicroRNA::Target Regulatory Interactions by Computing Technologies
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    Chapter 10 The Limitations of Existing Approaches in Improving MicroRNA Target Prediction Accuracy.
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    Chapter 11 Genomic Regulation of MicroRNA Expression in Disease Development
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    Chapter 12 Next-Generation Sequencing for MicroRNA Expression Profile
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    Chapter 13 Handling High-Dimension (High-Feature) MicroRNA Data.
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    Chapter 14 Effective Removal of Noisy Data Via Batch Effect Processing
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    Chapter 15 Logical Reasoning (Inferencing) on MicroRNA Data
  17. Altmetric Badge
    Chapter 16 Machine Learning Techniques in Exploring MicroRNA Gene Discovery, Targets, and Functions
  18. Altmetric Badge
    Chapter 17 Involvement of MicroRNAs in Diabetes and Its Complications
  19. Altmetric Badge
    Chapter 18 MicroRNA Regulatory Networks as Biomarkers in Obesity: The Emerging Role.
  20. Altmetric Badge
    Chapter 19 Expression of MicroRNAs in Thyroid Carcinoma.
Attention for Chapter 12: Next-Generation Sequencing for MicroRNA Expression Profile
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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1 Wikipedia page

Citations

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Chapter title
Next-Generation Sequencing for MicroRNA Expression Profile
Chapter number 12
Book title
Bioinformatics in MicroRNA Research
Published in
Methods in molecular biology, May 2017
DOI 10.1007/978-1-4939-7046-9_12
Pubmed ID
Book ISBNs
978-1-4939-7044-5, 978-1-4939-7046-9
Authors

Hu, Yue, Lan, Wenjun, Miller, Daniel, Yue Hu, Wenjun Lan Ph.D., Daniel Miller, Wenjun Lan

Editors

Jingshan Huang, Glen M. Borchert, Dejing Dou, Jun (Luke) Huan, Wenjun Lan, Ming Tan, Bin Wu

Abstract

Sequencing technologies have made considerable advancements. From the Sanger sequencing method to the next-generation sequencing (NGS) methods, and from the NGS methods to the third-generation sequencing methods, we can see the development thread of the sequencing technology. Currently, NGS is the main contender in the sequencing market. NGS technologies provide an opportunity to research the microRNA (miRNA) expression profiles in detail. The NGS platforms have their own special characteristics, but share some main ideas. DNA sequencing via NGS is fundamental for RNA sequencing and miRNA sequencing. MiRNA sequencing has special characteristics. The pipeline of miRNA sequencing by NGS is explained in detail from the wet experiment to the dry experiment.

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

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 13%
Student > Ph. D. Student 8 11%
Researcher 7 10%
Student > Master 5 7%
Student > Doctoral Student 4 6%
Other 6 8%
Unknown 32 45%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 24%
Agricultural and Biological Sciences 3 4%
Medicine and Dentistry 3 4%
Computer Science 2 3%
Veterinary Science and Veterinary Medicine 2 3%
Other 11 15%
Unknown 33 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 01 March 2024.
All research outputs
#7,785,550
of 25,391,701 outputs
Outputs from Methods in molecular biology
#2,324
of 14,174 outputs
Outputs of similar age
#113,975
of 327,151 outputs
Outputs of similar age from Methods in molecular biology
#37
of 254 outputs
Altmetric has tracked 25,391,701 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 14,174 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 83% 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 327,151 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 64% of its contemporaries.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.