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Title |
Genome3D: A viewer-model framework for integrating and visualizing multi-scale epigenomic information within a three-dimensional genome
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Published in |
BMC Bioinformatics, September 2010
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DOI | 10.1186/1471-2105-11-444 |
Pubmed ID | |
Authors |
Thomas M Asbury, Matt Mitman, Jijun Tang, W Jim Zheng |
Abstract |
New technologies are enabling the measurement of many types of genomic and epigenomic information at scales ranging from the atomic to nuclear. Much of this new data is increasingly structural in nature, and is often difficult to coordinate with other data sets. There is a legitimate need for integrating and visualizing these disparate data sets to reveal structural relationships not apparent when looking at these data in isolation. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 29% |
United States | 2 | 29% |
Unknown | 3 | 43% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 4 | 57% |
Members of the public | 2 | 29% |
Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 6% |
France | 2 | 3% |
Belgium | 2 | 3% |
Canada | 2 | 3% |
Australia | 1 | 1% |
Brazil | 1 | 1% |
Japan | 1 | 1% |
Sweden | 1 | 1% |
Unknown | 65 | 81% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 21 | 26% |
Researcher | 17 | 21% |
Professor > Associate Professor | 8 | 10% |
Student > Master | 7 | 9% |
Other | 4 | 5% |
Other | 13 | 16% |
Unknown | 10 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 35 | 44% |
Computer Science | 16 | 20% |
Medicine and Dentistry | 7 | 9% |
Biochemistry, Genetics and Molecular Biology | 4 | 5% |
Mathematics | 3 | 4% |
Other | 5 | 6% |
Unknown | 10 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 19 June 2013.
All research outputs
#5,669,730
of 22,701,287 outputs
Outputs from BMC Bioinformatics
#2,110
of 7,254 outputs
Outputs of similar age
#26,862
of 94,171 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 53 outputs
Altmetric has tracked 22,701,287 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 7,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 70% 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 94,171 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 53 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 66% of its contemporaries.