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miRNA Biogenesis

Overview of attention for book
Cover of 'miRNA Biogenesis'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 High-Throughput Characterization of Primary microRNA Transcripts
  3. Altmetric Badge
    Chapter 2 Identifying Pri-miRNA Transcription Start Sites
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    Chapter 3 Metabolic Pulse-Chase RNA Labeling for pri-miRNA Processing Dynamics
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    Chapter 4 In Vitro System for Coupling RNAP II Transcription to Primary microRNA Processing and a Three-Way System for RNAP II Transcription/Splicing/microRNA Processing
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    Chapter 5 Purification of Microprocessor-Associated Factors
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    Chapter 6 Inhibiting Pri-miRNA Processing with Target Site Blockers
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    Chapter 7 MicroRNA Analysis Using the Quantitative Real-Time PCR Reaction
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    Chapter 8 MicroRNA Analysis Using Next-Generation Sequencing
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    Chapter 9 Identification of microRNA Precursor-Associated Proteins
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    Chapter 10 Analysis of 3′ End Modifications in microRNAs by High-Throughput Sequencing
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    Chapter 11 Uncovering the Stability of Mature miRNAs by 4-Thio-Uridine Metabolic Labeling
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    Chapter 12 Detection of microRNA-Target Interactions by Chimera PCR (ChimP)
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    Chapter 13 High-Quality Overlapping Paired-End Reads for the Detection of A-to-I Editing on Small RNA
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    Chapter 14 Targeting miRNA for Therapeutics Using a Micronome Based Method for Identification of miRNA-mRNA Pairs and Validation of Key Regulator miRNA
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    Chapter 15 Method for Detection of miRNAs in Non-Model Organisms with Unreported Database
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    Chapter 16 Detection and Verification of Mammalian Mirtrons by Northern Blotting
  18. Altmetric Badge
    Chapter 17 Detecting Agotrons in Ago CLIPseq Data
Attention for Chapter 2: Identifying Pri-miRNA Transcription Start Sites
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Chapter title
Identifying Pri-miRNA Transcription Start Sites
Chapter number 2
Book title
miRNA Biogenesis
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-8624-8_2
Pubmed ID
Book ISBNs
978-1-4939-8623-1, 978-1-4939-8624-8
Authors

Georgios Georgakilas, Nikos Perdikopanis, Artemis G. Hatzigeorgiou, Georgakilas, Georgios, Perdikopanis, Nikos, Hatzigeorgiou, Artemis G.

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that can regulate gene expression playing vital role in nearly all biological pathways. Even though miRNAs have been intensely studied for more than two decades, information regarding miRNA transcription regulation remains limited. The rapid cleavage of primary miRNA transcripts (pri-miRNAs) by Drosha in the nucleus hinders their identification with conventional RNA-seq approaches. Identifying the transcription start site (TSS) of miRNAs will enable genome-wide identification of their expression regulators, including transcription factors (TFs), other non-coding RNAs (ncRNAs) and epigenetic modifiers, providing significant breakthroughs in understanding the mechanisms underlying miRNA expression in development and disease. Here we present a protocol that utilizes microTSS, a versatile computational framework for accurate and single-nucleotide resolution miRNA TSS predictions as well as miRGen, a database of miRNA gene TSSs coupled with genome-wide maps of TF binding sites.

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X Demographics

The data shown below were collected from the profiles of 5 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 21%
Researcher 3 21%
Student > Master 3 21%
Student > Bachelor 1 7%
Student > Doctoral Student 1 7%
Other 0 0%
Unknown 3 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 29%
Biochemistry, Genetics and Molecular Biology 2 14%
Computer Science 2 14%
Nursing and Health Professions 1 7%
Medicine and Dentistry 1 7%
Other 0 0%
Unknown 4 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 02 July 2018.
All research outputs
#14,498,358
of 24,325,299 outputs
Outputs from Methods in molecular biology
#3,908
of 13,696 outputs
Outputs of similar age
#229,383
of 450,951 outputs
Outputs of similar age from Methods in molecular biology
#363
of 1,481 outputs
Altmetric has tracked 24,325,299 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,696 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 69% 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 450,951 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,481 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.