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Combining proteomics and transcriptome sequencing to identify active plant-cell-wall-degrading enzymes in a leaf beetle

Overview of attention for article published in BMC Genomics, November 2012
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Title
Combining proteomics and transcriptome sequencing to identify active plant-cell-wall-degrading enzymes in a leaf beetle
Published in
BMC Genomics, November 2012
DOI 10.1186/1471-2164-13-587
Pubmed ID
Authors

Roy Kirsch, Natalie Wielsch, Heiko Vogel, Aleš Svatoš, David G Heckel, Yannick Pauchet

Abstract

The primary plant cell wall is a complex mixture of polysaccharides and proteins encasing living plant cells. Among these polysaccharides, cellulose is the most abundant and useful biopolymer present on earth. These polysaccharides also represent a rich source of energy for organisms which have evolved the ability to degrade them. A growing body of evidence suggests that phytophagous beetles, mainly species from the superfamilies Chrysomeloidea and Curculionoidea, possess endogenous genes encoding complex and diverse families of so-called plant cell wall degrading enzymes (PCWDEs). The presence of these genes in phytophagous beetles may have been a key element in their success as herbivores. Here, we combined a proteomics approach and transcriptome sequencing to identify PCWDEs present in larval gut contents of the mustard leaf beetle, Phaedon cochleariae.

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

Geographical breakdown

Country Count As %
Germany 2 3%
France 1 1%
Austria 1 1%
Sweden 1 1%
Mexico 1 1%
Japan 1 1%
Unknown 73 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 28%
Researcher 15 19%
Student > Doctoral Student 6 8%
Student > Postgraduate 5 6%
Student > Master 5 6%
Other 16 20%
Unknown 11 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 57%
Biochemistry, Genetics and Molecular Biology 12 15%
Chemistry 4 5%
Environmental Science 3 4%
Unspecified 1 1%
Other 2 3%
Unknown 12 15%
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 08 November 2012.
All research outputs
#13,370,975
of 22,684,168 outputs
Outputs from BMC Genomics
#4,974
of 10,616 outputs
Outputs of similar age
#100,554
of 184,149 outputs
Outputs of similar age from BMC Genomics
#72
of 141 outputs
Altmetric has tracked 22,684,168 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 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 50% of its peers.
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 184,149 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 141 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.