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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
NSeq: a multithreaded Java application for finding positioned nucleosomes from sequencing data
|
|---|---|
| Published in |
Frontiers in Genetics, January 2013
|
| DOI | 10.3389/fgene.2012.00320 |
| Pubmed ID | |
| Authors |
Abhinav Nellore, Konstantin Bobkov, Elizabeth Howe, Aleksandr Pankov, Aaron Diaz, Jun S. Song |
| Abstract |
We introduce NSeq, a fast and efficient Java application for finding positioned nucleosomes from the high-throughput sequencing of MNase-digested mononucleosomal DNA. NSeq includes a user-friendly graphical interface, computes false discovery rates (FDRs) for candidate nucleosomes from Monte Carlo simulations, plots nucleosome coverage and centers, and exploits the availability of multiple processor cores by parallelizing its computations. Java binaries and source code are freely available at https://github.com/songlab/NSeq. The software is supported on all major platforms equipped with Java Runtime Environment 6 or later. |
Twitter Demographics
The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 10% |
| Spain | 1 | 5% |
| Unknown | 17 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 35% |
| Student > Ph. D. Student | 5 | 25% |
| Other | 2 | 10% |
| Professor | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 2 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 70% |
| Biochemistry, Genetics and Molecular Biology | 5 | 25% |
| Computer Science | 1 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 24 January 2013.
All research outputs
#14,741,936
of 22,691,736 outputs
Outputs from Frontiers in Genetics
#4,434
of 11,754 outputs
Outputs of similar age
#175,236
of 280,671 outputs
Outputs of similar age from Frontiers in Genetics
#175
of 319 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,754 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 54% 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 280,671 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 319 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.