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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Gall-ID: tools for genotyping gall-causing phytopathogenic bacteria
|
|---|---|
| Published in |
PeerJ, July 2016
|
| DOI | 10.7717/peerj.2222 |
| Pubmed ID | |
| Authors |
Edward W. Davis, Alexandra J. Weisberg, Javier F. Tabima, Niklaus J. Grunwald, Jeff H. Chang |
| Abstract |
Understanding the population structure and genetic diversity of plant pathogens, as well as the effect of agricultural practices on pathogen evolution, is important for disease management. Developments in molecular methods have contributed to increase the resolution for accurate pathogen identification, but those based on analysis of DNA sequences can be less straightforward to use. To address this, we developed Gall-ID, a web-based platform that uses DNA sequence information from 16S rDNA, multilocus sequence analysis and whole genome sequences to group disease-associated bacteria to their taxonomic units. Gall-ID was developed with a particular focus on gall-forming bacteria belonging to Agrobacterium, Pseudomonas savastanoi, Pantoea agglomerans, and Rhodococcus. Members of these groups of bacteria cause growth deformation of plants, and some are capable of infecting many species of field, orchard, and nursery crops. Gall-ID also enables the use of high-throughput sequencing reads to search for evidence for homologs of characterized virulence genes, and provides downloadable software pipelines for automating multilocus sequence analysis, analyzing genome sequences for average nucleotide identity, and constructing core genome phylogenies. Lastly, additional databases were included in Gall-ID to help determine the identity of other plant pathogenic bacteria that may be in microbial communities associated with galls or causative agents in other diseased tissues of plants. The URL for Gall-ID is http://gall-id.cgrb.oregonstate.edu/. |
X Demographics
The data shown below were collected from the profiles of 6 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 | 3 | 50% |
| Canada | 1 | 17% |
| Venezuela, Bolivarian Republic of | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 67% |
| Members of the public | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Unknown | 37 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 29% |
| Student > Ph. D. Student | 8 | 21% |
| Student > Master | 4 | 11% |
| Professor | 2 | 5% |
| Student > Doctoral Student | 2 | 5% |
| Other | 6 | 16% |
| Unknown | 5 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 32% |
| Biochemistry, Genetics and Molecular Biology | 7 | 18% |
| Environmental Science | 3 | 8% |
| Mathematics | 2 | 5% |
| Chemical Engineering | 1 | 3% |
| Other | 5 | 13% |
| Unknown | 8 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 26 August 2016.
All research outputs
#2,930,752
of 24,885,505 outputs
Outputs from PeerJ
#3,045
of 14,829 outputs
Outputs of similar age
#51,690
of 371,618 outputs
Outputs of similar age from PeerJ
#69
of 310 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,829 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.0. This one has done well, scoring higher than 79% 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 371,618 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 310 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.