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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Bee Microbiome: Impact on Bee Health and Model for Evolution and Ecology of Host-Microbe Interactions
|
|---|---|
| Published in |
mBio, April 2016
|
| DOI | 10.1128/mbio.02164-15 |
| Pubmed ID | |
| Authors |
Philipp Engel, Waldan K. Kwong, Quinn McFrederick, Kirk E. Anderson, Seth Michael Barribeau, James Angus Chandler, R. Scott Cornman, Jacques Dainat, Joachim R. de Miranda, Vincent Doublet, Olivier Emery, Jay D. Evans, Laurent Farinelli, Michelle L. Flenniken, Fredrik Granberg, Juris A. Grasis, Laurent Gauthier, Juliette Hayer, Hauke Koch, Sarah Kocher, Vincent G. Martinson, Nancy Moran, Monica Munoz-Torres, Irene Newton, Robert J. Paxton, Eli Powell, Ben M. Sadd, Paul Schmid-Hempel, Regula Schmid-Hempel, Jin Song, Ryan S. Schwarz, Dennis vanEngelsdorp, Benjamin Dainat |
| Abstract |
As pollinators, bees are cornerstones for terrestrial ecosystem stability and key components in agricultural productivity. All animals, including bees, are associated with a diverse community of microbes, commonly referred to as the microbiome. The bee microbiome is likely to be a crucial factor affecting host health. However, with the exception of a few pathogens, the impacts of most members of the bee microbiome on host health are poorly understood. Further, the evolutionary and ecological forces that shape and change the microbiome are unclear. Here, we discuss recent progress in our understanding of the bee microbiome, and we present challenges associated with its investigation. We conclude that global coordination of research efforts is needed to fully understand the complex and highly dynamic nature of the interplay between the bee microbiome, its host, and the environment. High-throughput sequencing technologies are ideal for exploring complex biological systems, including host-microbe interactions. To maximize their value and to improve assessment of the factors affecting bee health, sequence data should be archived, curated, and analyzed in ways that promote the synthesis of different studies. To this end, the BeeBiome consortium aims to develop an online database which would provide reference sequences, archive metadata, and host analytical resources. The goal would be to support applied and fundamental research on bees and their associated microbes and to provide a collaborative framework for sharing primary data from different research programs, thus furthering our understanding of the bee microbiome and its impact on pollinator health. |
X Demographics
The data shown below were collected from the profiles of 30 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 37% |
| United Kingdom | 2 | 7% |
| Brazil | 2 | 7% |
| Ecuador | 1 | 3% |
| Australia | 1 | 3% |
| France | 1 | 3% |
| Spain | 1 | 3% |
| Sweden | 1 | 3% |
| Canada | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 9 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 21 | 70% |
| Scientists | 8 | 27% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 561 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | <1% |
| Colombia | 1 | <1% |
| Switzerland | 1 | <1% |
| Germany | 1 | <1% |
| Spain | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 553 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 112 | 20% |
| Researcher | 82 | 15% |
| Student > Master | 80 | 14% |
| Student > Bachelor | 68 | 12% |
| Student > Doctoral Student | 24 | 4% |
| Other | 71 | 13% |
| Unknown | 124 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 239 | 43% |
| Biochemistry, Genetics and Molecular Biology | 76 | 14% |
| Environmental Science | 28 | 5% |
| Immunology and Microbiology | 22 | 4% |
| Veterinary Science and Veterinary Medicine | 8 | 1% |
| Other | 37 | 7% |
| Unknown | 151 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 273. 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 April 2020.
All research outputs
#131,056
of 25,374,917 outputs
Outputs from mBio
#79
of 6,508 outputs
Outputs of similar age
#2,462
of 312,368 outputs
Outputs of similar age from mBio
#5
of 122 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,508 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.0. This one has done particularly well, scoring higher than 98% 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 312,368 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 122 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.