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RNA Interference

Overview of attention for book
Cover of 'RNA Interference'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 RNA interference: mechanisms, technical challenges, and therapeutic opportunities.
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    Chapter 2 Nanostructured RNAs for RNA Interference
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    Chapter 3 One Long Oligonucleotide or Two Short Oligonucleotides Based shRNA Construction and Expression
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    Chapter 4 PLGA Microspheres Encapsulating siRNA
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    Chapter 5 Magnetic Nanoparticle and Magnetic Field Assisted siRNA Delivery In Vitro
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    Chapter 6 Cytoplasmic Delivery of siRNAs to Monocytes and Dendritic Cells via Electroporation
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    Chapter 7 Delivery of siRNAs to Cancer Cells via Bacteria
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    Chapter 8 Microwell array-mediated delivery of lipoplexes containing nucleic acids for enhanced therapeutic efficacy.
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    Chapter 9 Modulating the Tumor Microenvironment with RNA Interference as a Cancer Treatment Strategy
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    Chapter 10 Targeted In Vivo Delivery of siRNA and an Endosome-Releasing Agent to Hepatocytes.
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    Chapter 11 Cell-Internalization SELEX: Method for Identifying Cell-Internalizing RNA Aptamers for Delivering siRNAs to Target Cells.
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    Chapter 12 Strategies for siRNA Navigation to Desired Cells.
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    Chapter 13 Use of Guanidinopropyl-Modified siRNAs to Silence Gene Expression
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    Chapter 14 Therapy of Respiratory Viral Infections with Intranasal siRNAs
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    Chapter 15 Engineering therapeutic cancer vaccines that activate antitumor immunity.
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    Chapter 16 Immunosuppressive Factor Blockade in Dendritic Cells via siRNAs Results in Objective Clinical Responses.
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    Chapter 17 Targeting bcr-abl Transcripts with siRNAs in an Imatinib-Resistant Chronic Myeloid Leukemia Patient: Challenges and Future Directions.
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    Chapter 18 A facile method for interfering with off-target silencing mediated by the sense strand.
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    Chapter 19 Overcoming the Challenges of siRNA Activation of Innate Immunity: Design Better Therapeutic siRNAs.
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    Chapter 20 Gene Silencing In Vitro and In Vivo Using Intronic MicroRNAs.
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    Chapter 21 In Silico Identification of Novel Endo-siRNAs.
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    Chapter 22 Computer-Assisted Annotation of Small RNA Transcriptomes
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    Chapter 23 miR-CATCH: MicroRNA Capture Affinity Technology.
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    Chapter 24 Roles of MicroRNAs in Cancers and Development.
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    Chapter 25 Targeting MicroRNAs to Withstand Cancer Metastasis.
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    Chapter 26 Urinary MicroRNAs as a New Class of Noninvasive Biomarkers in Oncology, Nephrology, and Cardiology.
  28. Altmetric Badge
    Chapter 27 Magnetic Bead-Based Isolation of Exosomes
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    Chapter 28 Modified 2'-Ribose Small RNAs Function as Toll-Like Receptor-7/8 Antagonists.
Attention for Chapter 22: Computer-Assisted Annotation of Small RNA Transcriptomes
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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Chapter title
Computer-Assisted Annotation of Small RNA Transcriptomes
Chapter number 22
Book title
RNA Interference
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-1538-5_22
Pubmed ID
Book ISBNs
978-1-4939-1537-8, 978-1-4939-1538-5
Authors

Nicole Ortogero, Grant W Hennig, Dickson Luong, Wei Yan, Grant W. Hennig, Ortogero, Nicole, Hennig, Grant W., Luong, Dickson, Yan, Wei

Abstract

Small noncoding RNAs (sncRNAs) are widely expressed in the cell of almost all known species. Most sncRNAs appear to have regulatory roles, ranging from facilitating RNA production and modifications (e.g., snoRNAs) to control of mRNA stability and translational efficiency (e.g., miRNAs and endo-siRNA) and to transposon silencing (e.g., piRNAs). The affordability and efficiency of next-generation RNA deep sequencing (RNA-Seq) technologies have made sncRNA deep sequencing (sncRNA-Seq) analyses a routine in biomedical research. SncRNA-Seq analyses generate millions of reads and gigabytes of data; annotation of sncRNA-Seq data remains challenging due to a lack of comprehensive sncRNA annotation pipelines. To solve this problem, we have developed a computer-assisted sncRNA annotation pipeline, which uses open-source software and allows for not only proper classification of known sncRNAs, but also discovery of novel sncRNA species. In this chapter, we describe our sncRNA annotation protocol in detail.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 45%
Student > Bachelor 2 18%
Student > Ph. D. Student 1 9%
Professor 1 9%
Professor > Associate Professor 1 9%
Other 1 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 36%
Agricultural and Biological Sciences 4 36%
Medicine and Dentistry 2 18%
Unknown 1 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 17 June 2015.
All research outputs
#3,547,183
of 22,766,595 outputs
Outputs from Methods in molecular biology
#848
of 13,090 outputs
Outputs of similar age
#50,774
of 352,895 outputs
Outputs of similar age from Methods in molecular biology
#48
of 996 outputs
Altmetric has tracked 22,766,595 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,090 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 93% 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 352,895 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 85% of its contemporaries.
We're also able to compare this research output to 996 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 95% of its contemporaries.