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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A novel approach for multi-domain and multi-gene family identification provides insights into evolutionary dynamics of disease resistance genes in core eudicot plants
|
|---|---|
| Published in |
BMC Genomics, November 2014
|
| DOI | 10.1186/1471-2164-15-966 |
| Pubmed ID | |
| Authors |
Johannes A Hofberger, Beifei Zhou, Haibao Tang, Jonathan DG Jones, M Eric Schranz |
| Abstract |
Recent advances in DNA sequencing techniques resulted in more than forty sequenced plant genomes representing a diverse set of taxa of agricultural, energy, medicinal and ecological importance. However, gene family curation is often only inferred from DNA sequence homology and lacks insights into evolutionary processes contributing to gene family dynamics. In a comparative genomics framework, we integrated multiple lines of evidence provided by gene synteny, sequence homology and protein-based Hidden Markov Modelling to extract homologous super-clusters composed of multi-domain resistance (R)-proteins of the NB-LRR type (for NUCLEOTIDE BINDING/LEUCINE-RICH REPEATS), that are involved in plant innate immunity. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| South Africa | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 2% |
| United States | 1 | 1% |
| Unknown | 86 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 29% |
| Researcher | 21 | 24% |
| Professor > Associate Professor | 7 | 8% |
| Student > Master | 6 | 7% |
| Student > Bachelor | 5 | 6% |
| Other | 14 | 16% |
| Unknown | 10 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 49 | 55% |
| Biochemistry, Genetics and Molecular Biology | 17 | 19% |
| Computer Science | 2 | 2% |
| Engineering | 2 | 2% |
| Environmental Science | 1 | 1% |
| Other | 4 | 4% |
| Unknown | 14 | 16% |
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 10 February 2015.
All research outputs
#17,731,162
of 22,769,322 outputs
Outputs from BMC Genomics
#7,551
of 10,639 outputs
Outputs of similar age
#177,610
of 263,177 outputs
Outputs of similar age from BMC Genomics
#196
of 287 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,639 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 23rd percentile – i.e., 23% 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 263,177 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 287 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.