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X Demographics
Mendeley readers
Attention Score in Context
| Title |
HgtSIM: a simulator for horizontal gene transfer (HGT) in microbial communities
|
|---|---|
| Published in |
PeerJ, November 2017
|
| DOI | 10.7717/peerj.4015 |
| Pubmed ID | |
| Authors |
Weizhi Song, Kerrin Steensen, Torsten Thomas |
| Abstract |
The development and application of metagenomic approaches have provided an opportunity to study and define horizontal gene transfer (HGT) on the level of microbial communities. However, no current metagenomic data simulation tools offers the option to introduce defined HGT within a microbial community. Here, we present HgtSIM, a pipeline to simulate HGT event among microbial community members with user-defined mutation levels. It was developed for testing and benchmarking pipelines for recovering HGTs from complex microbial datasets. HgtSIM is implemented in Python3 and is freely available at: https://github.com/songweizhi/HgtSIM. |
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 % |
|---|---|---|
| New Zealand | 1 | 17% |
| India | 1 | 17% |
| Australia | 1 | 17% |
| Unknown | 3 | 50% |
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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 25% |
| Student > Master | 4 | 17% |
| Student > Ph. D. Student | 3 | 13% |
| Student > Bachelor | 3 | 13% |
| Lecturer | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 6 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 25% |
| Agricultural and Biological Sciences | 6 | 25% |
| Computer Science | 2 | 8% |
| Engineering | 2 | 8% |
| Unknown | 8 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 2019.
All research outputs
#2,071,395
of 23,550,886 outputs
Outputs from PeerJ
#2,289
of 13,813 outputs
Outputs of similar age
#42,880
of 332,815 outputs
Outputs of similar age from PeerJ
#85
of 369 outputs
Altmetric has tracked 23,550,886 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,813 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.3. 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 332,815 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 87% of its contemporaries.
We're also able to compare this research output to 369 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.