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Adaptable data management for systems biology investigations

Overview of attention for article published in BMC Bioinformatics, March 2009
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Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
109 Mendeley
citeulike
13 CiteULike
connotea
2 Connotea
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Title
Adaptable data management for systems biology investigations
Published in
BMC Bioinformatics, March 2009
DOI 10.1186/1471-2105-10-79
Pubmed ID
Authors

John Boyle, Hector Rovira, Chris Cavnor, David Burdick, Sarah Killcoyne, Ilya Shmulevich

Abstract

Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage.

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.

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Sweden 3 3%
United Kingdom 3 3%
Portugal 2 2%
Hong Kong 1 <1%
Australia 1 <1%
Germany 1 <1%
Italy 1 <1%
New Zealand 1 <1%
Other 4 4%
Unknown 88 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 32%
Student > Ph. D. Student 21 19%
Student > Master 14 13%
Other 10 9%
Professor 6 6%
Other 17 16%
Unknown 6 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 48%
Computer Science 19 17%
Biochemistry, Genetics and Molecular Biology 13 12%
Medicine and Dentistry 10 9%
Chemistry 2 2%
Other 6 6%
Unknown 7 6%

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 11 May 2015.
All research outputs
#7,141,717
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#2,781
of 4,576 outputs
Outputs of similar age
#103,445
of 223,349 outputs
Outputs of similar age from BMC Bioinformatics
#117
of 194 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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 223,349 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 50% of its contemporaries.
We're also able to compare this research output to 194 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.