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X Demographics
Mendeley readers
Attention Score in Context
Title |
The Gaggle: An open-source software system for integrating bioinformatics software and data sources
|
---|---|
Published in |
BMC Bioinformatics, March 2006
|
DOI | 10.1186/1471-2105-7-176 |
Pubmed ID | |
Authors |
Paul T Shannon, David J Reiss, Richard Bonneau, Nitin S Baliga |
Abstract |
Systems biologists work with many kinds of data, from many different sources, using a variety of software tools. Each of these tools typically excels at one type of analysis, such as of microarrays, of metabolic networks and of predicted protein structure. A crucial challenge is to combine the capabilities of these (and other forthcoming) data resources and tools to create a data exploration and analysis environment that does justice to the variety and complexity of systems biology data sets. A solution to this problem should recognize that data types, formats and software in this high throughput age of biology are constantly changing. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Cameroon | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 229 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 5% |
United Kingdom | 6 | 3% |
Brazil | 4 | 2% |
Germany | 3 | 1% |
Canada | 3 | 1% |
Sweden | 3 | 1% |
France | 2 | <1% |
Spain | 2 | <1% |
Japan | 2 | <1% |
Other | 12 | 5% |
Unknown | 180 | 79% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 72 | 31% |
Student > Ph. D. Student | 43 | 19% |
Student > Master | 24 | 10% |
Other | 16 | 7% |
Professor > Associate Professor | 16 | 7% |
Other | 40 | 17% |
Unknown | 18 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 120 | 52% |
Computer Science | 32 | 14% |
Biochemistry, Genetics and Molecular Biology | 22 | 10% |
Medicine and Dentistry | 13 | 6% |
Engineering | 6 | 3% |
Other | 15 | 7% |
Unknown | 21 | 9% |
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 13 March 2024.
All research outputs
#6,407,067
of 25,478,886 outputs
Outputs from BMC Bioinformatics
#2,134
of 7,706 outputs
Outputs of similar age
#24,112
of 85,431 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 56 outputs
Altmetric has tracked 25,478,886 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 7,706 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 71% 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 85,431 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 56 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 60% of its contemporaries.