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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Exploring Massive, Genome Scale Datasets with the GenometriCorr Package
|
|---|---|
| Published in |
PLoS Computational Biology, May 2012
|
| DOI | 10.1371/journal.pcbi.1002529 |
| Pubmed ID | |
| Authors |
Alexander Favorov, Loris Mularoni, Leslie M. Cope, Yulia Medvedeva, Andrey A. Mironov, Vsevolod J. Makeev, Sarah J. Wheelan |
| Abstract |
We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. |
X Demographics
The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 27% |
| Germany | 2 | 9% |
| France | 1 | 5% |
| Australia | 1 | 5% |
| Netherlands | 1 | 5% |
| India | 1 | 5% |
| Grenada | 1 | 5% |
| Japan | 1 | 5% |
| United Kingdom | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 6 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 13 | 59% |
| Members of the public | 8 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 220 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 3% |
| Spain | 3 | 1% |
| United Kingdom | 2 | <1% |
| Netherlands | 1 | <1% |
| Australia | 1 | <1% |
| Sweden | 1 | <1% |
| Denmark | 1 | <1% |
| Switzerland | 1 | <1% |
| Brazil | 1 | <1% |
| Other | 3 | 1% |
| Unknown | 200 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 72 | 33% |
| Student > Ph. D. Student | 54 | 25% |
| Student > Master | 16 | 7% |
| Student > Bachelor | 13 | 6% |
| Professor > Associate Professor | 12 | 5% |
| Other | 43 | 20% |
| Unknown | 10 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 125 | 57% |
| Biochemistry, Genetics and Molecular Biology | 45 | 20% |
| Computer Science | 10 | 5% |
| Medicine and Dentistry | 7 | 3% |
| Immunology and Microbiology | 4 | 2% |
| Other | 13 | 6% |
| Unknown | 16 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 25 May 2018.
All research outputs
#3,202,241
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#2,831
of 8,960 outputs
Outputs of similar age
#20,682
of 179,085 outputs
Outputs of similar age from PLoS Computational Biology
#24
of 109 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 68% 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 179,085 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 88% of its contemporaries.
We're also able to compare this research output to 109 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.