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Deep mRNA sequencing reveals stage-specific transcriptome alterations during microsclerotia development in the smoke tree vascular wilt pathogen, Verticillium dahliae

Overview of attention for article published in BMC Genomics, May 2014
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Title
Deep mRNA sequencing reveals stage-specific transcriptome alterations during microsclerotia development in the smoke tree vascular wilt pathogen, Verticillium dahliae
Published in
BMC Genomics, May 2014
DOI 10.1186/1471-2164-15-324
Pubmed ID
Authors

Dianguang Xiong, Yonglin Wang, Jie Ma, Steven J Klosterman, Shuxiao Xiao, Chengming Tian

Abstract

Verticillium dahliae is a soil-borne fungus that causes vascular wilt diseases in a wide range of plant hosts. V. dahliae produces multicelled, melanized resting bodies, also known as microsclerotia (MS) that can survive for years in the soil. The MS are the primary source of infection of the Verticillium disease cycle. Thus, MS formation marks an important event in the disease cycle of V. dahliae.

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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 2%
Unknown 57 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 38%
Researcher 12 21%
Student > Doctoral Student 3 5%
Student > Bachelor 3 5%
Student > Master 3 5%
Other 6 10%
Unknown 9 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 62%
Biochemistry, Genetics and Molecular Biology 10 17%
Immunology and Microbiology 1 2%
Social Sciences 1 2%
Engineering 1 2%
Other 0 0%
Unknown 9 16%
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 15 May 2014.
All research outputs
#14,726,276
of 24,694,993 outputs
Outputs from BMC Genomics
#5,301
of 11,047 outputs
Outputs of similar age
#117,558
of 232,957 outputs
Outputs of similar age from BMC Genomics
#71
of 186 outputs
Altmetric has tracked 24,694,993 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 11,047 research outputs from this source. They receive a mean Attention Score of 4.8. 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 232,957 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 186 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 60% of its contemporaries.