↓ Skip to main content

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

Overview of attention for article published in BMC Plant Biology, February 2008
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
432 Dimensions

Readers on

mendeley
251 Mendeley
citeulike
3 CiteULike
connotea
1 Connotea
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Identification of novel and candidate miRNAs in rice by high throughput sequencing
Published in
BMC Plant Biology, February 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.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 251 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 231 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 78 31%
Researcher 54 22%
Student > Master 19 8%
Professor > Associate Professor 15 6%
Professor 13 5%
Other 42 17%
Unknown 30 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 162 65%
Biochemistry, Genetics and Molecular Biology 29 12%
Computer Science 12 5%
Medicine and Dentistry 2 <1%
Mathematics 2 <1%
Other 7 3%
Unknown 37 15%
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 20 December 2012.
All research outputs
#20,656,161
of 25,374,647 outputs
Outputs from BMC Plant Biology
#2,377
of 3,588 outputs
Outputs of similar age
#87,834
of 94,795 outputs
Outputs of similar age from BMC Plant Biology
#7
of 7 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,588 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 21st percentile – i.e., 21% 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 94,795 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.