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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GemSIM: general, error-model based simulator of next-generation sequencing data
|
|---|---|
| Published in |
BMC Genomics, February 2012
|
| DOI | 10.1186/1471-2164-13-74 |
| Pubmed ID | |
| Authors |
Kerensa E McElroy, Fabio Luciani, Torsten Thomas |
| Abstract |
GemSIM, or General Error-Model based SIMulator, is a next-generation sequencing simulator capable of generating single or paired-end reads for any sequencing technology compatible with the generic formats SAM and FASTQ (including Illumina and Roche/454). GemSIM creates and uses empirically derived, sequence-context based error models to realistically emulate individual sequencing runs and/or technologies. Empirical fragment length and quality score distributions are also used. Reads may be drawn from one or more genomes or haplotype sets, facilitating simulation of deep sequencing, metagenomic, and resequencing projects. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 40% |
| Sweden | 1 | 20% |
| Spain | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 283 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 12 | 4% |
| Germany | 5 | 2% |
| United Kingdom | 5 | 2% |
| France | 4 | 1% |
| Norway | 2 | <1% |
| Italy | 2 | <1% |
| Sweden | 2 | <1% |
| Taiwan | 2 | <1% |
| Spain | 2 | <1% |
| Other | 9 | 3% |
| Unknown | 238 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 86 | 30% |
| Student > Ph. D. Student | 78 | 28% |
| Student > Master | 23 | 8% |
| Student > Bachelor | 22 | 8% |
| Professor > Associate Professor | 13 | 5% |
| Other | 47 | 17% |
| Unknown | 14 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 154 | 54% |
| Computer Science | 42 | 15% |
| Biochemistry, Genetics and Molecular Biology | 42 | 15% |
| Mathematics | 6 | 2% |
| Environmental Science | 5 | 2% |
| Other | 15 | 5% |
| Unknown | 19 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 09 July 2012.
All research outputs
#7,959,659
of 25,371,288 outputs
Outputs from BMC Genomics
#3,479
of 11,244 outputs
Outputs of similar age
#69,159
of 258,155 outputs
Outputs of similar age from BMC Genomics
#37
of 103 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 67% 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 258,155 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.