↓ Skip to main content

BioAssay Ontology (BAO): a semantic description of bioassays and high-throughput screening results

Overview of attention for article published in BMC Bioinformatics, January 2011
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
72 Dimensions

Readers on

mendeley
86 Mendeley
citeulike
11 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
BioAssay Ontology (BAO): a semantic description of bioassays and high-throughput screening results
Published in
BMC Bioinformatics, January 2011
DOI 10.1186/1471-2105-12-257
Pubmed ID
Authors

Ubbo Visser, Saminda Abeyruwan, Uma Vempati, Robin P Smith, Vance Lemmon, Stephan C Schürer

Abstract

High-throughput screening (HTS) is one of the main strategies to identify novel entry points for the development of small molecule chemical probes and drugs and is now commonly accessible to public sector research. Large amounts of data generated in HTS campaigns are submitted to public repositories such as PubChem, which is growing at an exponential rate. The diversity and quantity of available HTS assays and screening results pose enormous challenges to organizing, standardizing, integrating, and analyzing the datasets and thus to maximize the scientific and ultimately the public health impact of the huge investments made to implement public sector HTS capabilities. Novel approaches to organize, standardize and access HTS data are required to address these challenges.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 5%
United Kingdom 3 3%
Netherlands 2 2%
Brazil 2 2%
Bulgaria 1 1%
France 1 1%
Switzerland 1 1%
China 1 1%
Japan 1 1%
Other 1 1%
Unknown 69 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 31%
Student > Ph. D. Student 17 20%
Student > Master 7 8%
Professor 7 8%
Other 6 7%
Other 18 21%
Unknown 4 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 28%
Computer Science 21 24%
Chemistry 11 13%
Engineering 6 7%
Medicine and Dentistry 5 6%
Other 12 14%
Unknown 7 8%

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 25 March 2016.
All research outputs
#6,106,497
of 11,350,565 outputs
Outputs from BMC Bioinformatics
#2,313
of 4,199 outputs
Outputs of similar age
#52,215
of 114,368 outputs
Outputs of similar age from BMC Bioinformatics
#43
of 87 outputs
Altmetric has tracked 11,350,565 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,199 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 42nd percentile – i.e., 42% 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 114,368 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 52% of its contemporaries.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.