↓ Skip to main content

Transcriptomic analysis of the phytopathogenic oomycete Phytophthora cactorum provides insights into infection-related effectors

Overview of attention for article published in BMC Genomics, November 2014
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
82 Mendeley
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
Transcriptomic analysis of the phytopathogenic oomycete Phytophthora cactorum provides insights into infection-related effectors
Published in
BMC Genomics, November 2014
DOI 10.1186/1471-2164-15-980
Pubmed ID
Authors

Xiao-Ren Chen, Bo-Yue Zhang, Yu-Ping Xing, Qi-Yuan Li, Yan-Peng Li, Yun-Hui Tong, Jing-You Xu

Abstract

Phytophthora cactorum, a hemibiotrophic oomycete pathogen, can cause destructive diseases on numerous crops worldwide, leading to essential economic losses every year. However, little has been known about its molecular pathogenicity mechanisms. To gain insight into its repertoire of effectors, the P. cactorum transcriptome was investigated using Illumina RNA-seq.

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

Geographical breakdown

Country Count As %
Mexico 1 1%
Unknown 81 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 22%
Student > Master 13 16%
Researcher 12 15%
Student > Bachelor 8 10%
Student > Doctoral Student 6 7%
Other 10 12%
Unknown 15 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 55%
Biochemistry, Genetics and Molecular Biology 10 12%
Environmental Science 2 2%
Immunology and Microbiology 2 2%
Engineering 2 2%
Other 4 5%
Unknown 17 21%
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 18 November 2014.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from BMC Genomics
#9,840
of 11,244 outputs
Outputs of similar age
#315,990
of 369,893 outputs
Outputs of similar age from BMC Genomics
#325
of 362 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% 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 369,893 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 362 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.