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Identification of novel and candidate miRNAs in rice by high throughput sequencing

Overview of attention for article published in BMC Plant Biology, January 2008
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Mentioned by

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1 tweeter

Citations

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420 Dimensions

Readers on

mendeley
239 Mendeley
citeulike
3 CiteULike
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1 Connotea
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Title
Identification of novel and candidate miRNAs in rice by high throughput sequencing
Published in
BMC Plant Biology, January 2008
DOI 10.1186/1471-2229-8-25
Pubmed ID
Authors

Ramanjulu Sunkar, Xuefeng Zhou, Yun Zheng, Weixiong Zhang, Jian-Kang Zhu

Abstract

Small RNA-guided gene silencing at the transcriptional and post-transcriptional levels has emerged as an important mode of gene regulation in plants and animals. Thus far, conventional sequencing of small RNA libraries from rice led to the identification of most of the conserved miRNAs. Deep sequencing of small RNA libraries is an effective approach to uncover rare and lineage- and/or species-specific microRNAs (miRNAs) in any organism.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 239 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
Brazil 3 1%
France 2 <1%
India 2 <1%
United Kingdom 2 <1%
China 2 <1%
Sweden 1 <1%
Norway 1 <1%
Italy 1 <1%
Other 2 <1%
Unknown 219 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 78 33%
Researcher 53 22%
Student > Master 18 8%
Professor > Associate Professor 16 7%
Professor 12 5%
Other 40 17%
Unknown 22 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 160 67%
Biochemistry, Genetics and Molecular Biology 28 12%
Computer Science 12 5%
Mathematics 3 1%
Medicine and Dentistry 2 <1%
Other 6 3%
Unknown 28 12%

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 20 December 2012.
All research outputs
#9,050,203
of 11,307,883 outputs
Outputs from BMC Plant Biology
#895
of 1,358 outputs
Outputs of similar age
#218,400
of 310,206 outputs
Outputs of similar age from BMC Plant Biology
#29
of 42 outputs
Altmetric has tracked 11,307,883 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,358 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.