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Attention Score in Context
| Title |
Deep RNA sequencing of L. monocytogenes reveals overlapping and extensive stationary phase and sigma B-dependent transcriptomes, including multiple highly transcribed noncoding RNAs
|
|---|---|
| Published in |
BMC Genomics, December 2009
|
| DOI | 10.1186/1471-2164-10-641 |
| Pubmed ID | |
| Authors |
Haley F Oliver, Renato H Orsi, Lalit Ponnala, Uri Keich, Wei Wang, Qi Sun, Samuel W Cartinhour, Melanie J Filiatrault, Martin Wiedmann, Kathryn J Boor |
| Abstract |
Identification of specific genes and gene expression patterns important for bacterial survival, transmission and pathogenesis is critically needed to enable development of more effective pathogen control strategies. The stationary phase stress response transcriptome, including many sigmaB-dependent genes, was defined for the human bacterial pathogen Listeria monocytogenes using RNA sequencing (RNA-Seq) with the Illumina Genome Analyzer. Specifically, bacterial transcriptomes were compared between stationary phase cells of L. monocytogenes 10403S and an otherwise isogenic DeltasigB mutant, which does not express the alternative sigma factor sigmaB, a major regulator of genes contributing to stress response, including stresses encountered upon entry into stationary phase. |
Mendeley readers
The data shown below were compiled from readership statistics for 192 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 3% |
| United Kingdom | 3 | 2% |
| France | 2 | 1% |
| Netherlands | 1 | <1% |
| Italy | 1 | <1% |
| Germany | 1 | <1% |
| Sweden | 1 | <1% |
| Denmark | 1 | <1% |
| Mexico | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 175 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 50 | 26% |
| Researcher | 47 | 24% |
| Student > Master | 16 | 8% |
| Student > Bachelor | 12 | 6% |
| Student > Doctoral Student | 11 | 6% |
| Other | 41 | 21% |
| Unknown | 15 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 111 | 58% |
| Biochemistry, Genetics and Molecular Biology | 24 | 13% |
| Immunology and Microbiology | 18 | 9% |
| Medicine and Dentistry | 4 | 2% |
| Engineering | 3 | 2% |
| Other | 14 | 7% |
| Unknown | 18 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 01 June 2014.
All research outputs
#4,165,117
of 22,757,090 outputs
Outputs from BMC Genomics
#1,740
of 10,637 outputs
Outputs of similar age
#23,765
of 163,791 outputs
Outputs of similar age from BMC Genomics
#19
of 118 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 83% 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 163,791 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 84% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.