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RNA-Seq analysis reveals new gene models and alternative splicing in the fungal pathogen Fusarium graminearum

Overview of attention for article published in BMC Genomics, January 2013
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3 X users

Citations

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75 Dimensions

Readers on

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178 Mendeley
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3 CiteULike
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Title
RNA-Seq analysis reveals new gene models and alternative splicing in the fungal pathogen Fusarium graminearum
Published in
BMC Genomics, January 2013
DOI 10.1186/1471-2164-14-21
Pubmed ID
Authors

Chunzhao Zhao, Cees Waalwijk, Pierre J G M de Wit, Dingzhong Tang, Theo van der Lee

Abstract

The genome of Fusarium graminearum has been sequenced and annotated previously, but correct gene annotation remains a challenge. In addition, posttranscriptional regulations, such as alternative splicing and RNA editing, are poorly understood in F. graminearum. Here we took advantage of RNA-Seq to improve gene annotations and to identify alternative splicing and RNA editing in F. graminearum.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 1%
Australia 2 1%
Germany 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
United States 1 <1%
Unknown 170 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 61 34%
Researcher 39 22%
Student > Master 20 11%
Student > Doctoral Student 14 8%
Student > Bachelor 10 6%
Other 20 11%
Unknown 14 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 107 60%
Biochemistry, Genetics and Molecular Biology 34 19%
Computer Science 6 3%
Chemistry 3 2%
Environmental Science 2 1%
Other 6 3%
Unknown 20 11%
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 22 January 2013.
All research outputs
#13,679,281
of 22,693,205 outputs
Outputs from BMC Genomics
#5,264
of 10,616 outputs
Outputs of similar age
#164,134
of 284,968 outputs
Outputs of similar age from BMC Genomics
#186
of 364 outputs
Altmetric has tracked 22,693,205 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 49th percentile – i.e., 49% 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 284,968 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 364 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.