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Mendeley readers
Attention Score in Context
| Title |
Sociogenomics of self vs. non-self cooperation during development of Dictyostelium discoideum
|
|---|---|
| Published in |
BMC Genomics, July 2014
|
| DOI | 10.1186/1471-2164-15-616 |
| Pubmed ID | |
| Authors |
Si I Li, Neil J Buttery, Christopher RL Thompson, Michael D Purugganan |
| Abstract |
Dictyostelium discoideum, a microbial model for social evolution, is known to distinguish self from non-self and show genotype-dependent behavior during chimeric development. Aside from a small number of cell-cell recognition genes, however, little is known about the genetic basis of self/non-self recognition in this species. Based on the key hypothesis that there should be differential expression of genes if D. discoideum cells were interacting with non-clone mates, we performed transcriptomic profiling study in this species during clonal vs. chimeric development. The transcriptomic profiles of D. discoideum cells in clones vs. different chimeras were compared at five different developmental stages using a customized microarray. Effects of chimerism on global transcriptional patterns associated with social interactions were observed. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 4% |
| Mexico | 1 | 4% |
| Unknown | 23 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 24% |
| Student > Master | 6 | 24% |
| Researcher | 6 | 24% |
| Student > Ph. D. Student | 4 | 16% |
| Student > Doctoral Student | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 52% |
| Physics and Astronomy | 3 | 12% |
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Engineering | 2 | 8% |
| Computer Science | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 2 | 8% |
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 20 February 2015.
All research outputs
#20,262,276
of 22,792,160 outputs
Outputs from BMC Genomics
#9,273
of 10,648 outputs
Outputs of similar age
#192,516
of 228,636 outputs
Outputs of similar age from BMC Genomics
#173
of 205 outputs
Altmetric has tracked 22,792,160 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 10,648 research outputs from this source. They receive a mean Attention Score of 4.7. 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 228,636 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 205 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.